Sambot: A Self-Assembly Modular Robot System - IEEE Xplore

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE/ASME TRANSACTIONS ON MECHATRONICS

1

Sambot: A Self-Assembly Modular Robot System Hongxing Wei, Member, IEEE, Youdong Chen, Member, IEEE, Jindong Tan, Member, IEEE, and Tianmiao Wang, Member, IEEE

Abstract—The design and structure of a self-assembly modular robot (Sambot) are presented in this paper. Each module has its own autonomous mobility and can connect with other modules to form robotic structures with different manipulation abilities. Sambot has a versatile, robust, and flexible structure. The computing platform provided for each module is distributed and consists of a number of interlinked microcontrollers. The interaction and connectivity between different modules is achieved through infrared sensors and Zigbee wireless communication in discrete state and control area network bus communication in robotic configuration state. A new mechanical design is put forth to realize the autonomous motion and docking of Sambots. It is a challenge to integrate actuators, sensors, microprocessors, power units, and communication elements into a highly compact and flexible module with the overall size of 80 mm × 80 mm × 102 mm. The work describes represents a mature development in the area of self-assembly distributed robotics. Index Terms—Autonomous docking, modular robot, selfassembly, self-reconfiguration.

I. INTRODUCTION OTIVATED by the swarm behaviors of social insects, the research on self-assembly swarm robots has absorbed the attention of many researchers in the robotics community. Swarm robots, generally, refer to a large number of relatively simple robots, which have some desired collective behaviors resulting from local interactions among themselves and between them and the environments [1]. In insect societies, a number of striking collective structures can be formed by self-assembly. For instance, a swarm of ants may form a temporary bridge across a gap for the colony to pass by [2]. Self-assembly is a process of autonomously organizing preexisting components into patterns or structures without human intervention [3]. In a robotic system, self-assembly provides an effective and practical mode for the collaboration of multiple

M

Manuscript received March 3, 2010; revised July 26, 2010; accepted September 24, 2010. Recommended by Technical Editor J. Ueda. This work was supported in part by the 863 Program of China under Grant 2009AA043901 and Grant 2009AA043903, in part by the National Natural Science Foundation of China under Grant 60525314, and in part by the Beijing Technological New Star Project under Grant 2008A018. H. Wei is with the School of Mechanical Engineering and Automation, Beihang University, Beijing, 100191 China, and also with the Electrical Engineering Department, Michigan Technological University, Houghton, MI 49931 USA (e-mail: [email protected]). Y. Chen and T. Wang are with the School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China (e-mail: [email protected]; [email protected]). J. Tan is with the Electrical Engineering Department, Michigan Technological University, Houghton, MI 49931 USA (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TMECH.2010.2085009

robots. A group of modular units or individual robots with identical functions connect to form robotic structures with different functions and morphologies [4]. Compared to an individual modular unit and or an individual robot, the robotic structure has more powerful locomotion, sharper perception, and better working ability. For example, a snake-like robot can crawl through a narrow passage, or can self-assemble again into a quadruped robot, which can locomote more easily on rough terrain. Selfassembly robots are, particularly, useful for applications in unstructured, remote, and hazardous environments, such as deep sea and outer space. The combinations of swarm robots, selfassembly robots, and self-reconfigurable robots provide important ways to design new robotic systems, whose functions and morphologies can both evolve [5]. Now, few existing platforms of swarm robotics have selfassembly function. Due to their different design purposes, the locomotions of self-assembly robots are not the same as those of similar chain-type self-reconfigurable robots [6]. For modular self-reconfigurable robots, the basic unit modules usually do not move by themselves or only have very limited mobility. In some systems, the reconfiguration was demonstrated with the modules being prearranged at preset positions [7]. Researchers have planned to develop platforms with the characteristics of swarm robots, self-assembled robots, and self-reconfigurable robots [8]. However, to the best knowledge of the authors, there have been no successful prototypes up till now, due to the complexity of the integrated design of both the mechanical and control systems under the critical constraints of functions, sizes, and energy consumption. This paper presents the design of a novel self-assembly modular robot (Sambot) with the features of self-assembly and selfreconfiguration, that is to say, multiple Sambots can form a new robotic structure through self-assembly and self-reconfiguration [37]. Different from the designs of existing self-reconfigurable robots and swarm robots, we realized self-assembly function in Sambot by innovative design of the docking mechanism and reasonable distribution of the perception system. The docking mechanism is installed on an active docking interface, which can rotate around the main body of the robot. The locomotion and reconfiguration abilities are as good as those of the existing chain-type self-reconfigurable robots. Besides, the communication and power subsystems, the control units, actuators, and sensors are tightly integrated into the robot by optimizing the design of the mechatronic system. The overall size of a Sambot is only 80 mm × 80 mm × 102 mm and the weight is merely 400 gm. Sambot has been, so far, the first practical robotic platform that has integrated the characteristics of multirobots, self-assembly robots, and self-reconfigurable robots, to the best knowledge of the authors.

1083-4435/$26.00 © 2010 IEEE

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. 2

IEEE/ASME TRANSACTIONS ON MECHATRONICS

This paper is organized as follows. Section II reviews the existing design of swarm robots, self-reconfigurable robots, and self-assembly robots. Section III describes the design principles, the mechanical structure, the active docking system, and the electronic system of Sambot. Section IV gives Sambot’s control software design, including the control algorithms of Sambot’s autonomous docking and the gait control methods for the locomotion of a robotic structure composed of multiple Sambots. Section V presents experiments on autonomous docking and the whole locomotion of multiple Sambots. Section VI discusses the characteristics of Sambot in such aspects as structural design, self-assembly, self-reconfiguration, and locomotion. The last section summarizes the paper and gives some prospects for future work. II. RELATED WORK A. Swarm Robots Swarm robots are usually referred to as a multirobot system consisting of a great number of simple robots with identical functions. This kind of system can imitate the group behaviors of species in the nature, such as swarms of ants, schools of fishes, and flocks of birds. A swarm robot can realize the interaction and collaboration controls among the individual robots and between them and their surrounding environment [1]. Earlier research work included the swarm system developed by Beni [9], which is a distributed system composed of a great number of autonomous robots. These earlier robot modules only have low intelligence. Recently, most of the research on swarm robots has been focused on the collaboration (e.g., formation and transportation through collaboration) and self-organization controls of a robot group. The sizes of existing platforms of swarm robots range from dozens of millimeters to one hundred millimeters. The swarm robots, generally, have the abilities of autonomous motion and perception [10]–[14]. Some related research on the formation, traveling, and exploration approaches of swarm robotics has been made [15]–[20]. Franchi et al. developed the decentralized cooperative exploration strategy for a team of swarm robots [15]. Sariel-Talay et al. presented the algorithm and solution to deal with the problem of multiple travelling robots [16]. The tracking and formation problems have also been investigated [17]–[19]. Some robots adopted ZigBee as a way of wireless communication [11], [20]. Comparatively speaking, less research have been performed on self-assembly swarm robots. Swarm-bot is one of these few platforms [4], which is a homogeneous swarm robotic system composed of many autonomous robots called s-bot. The multiple s-bots self-assembled in this way are mainly used in transportation and collaborative evolutionary control research [6], [21]. However, s-bot does not have the locomotion ability of the chain-type self-reconfigurable robot system. B. Self-Reconfigurable Robots Self-reconfiguration is an automatic process to rearrange the modules. In a self-reconfigurable robot, the basic unit modules usually cannot move on their own or only have very lim-

ited ability of self-motion. Most of the research on existing self-reconfigurable robots are concerned with the docking, selfreconfiguration, and motion of the modules. The existing selfreconfigurable robots are divided into four kinds of structures: chain-based, lattice-based, mobile, and stochastic [4], [7]. In this paper, we mainly focus on the autonomous docking of self-reconfigurable robots. The autonomous docking of a selfreconfigurable robot usually relies on the collaboration between the modules, and is realized by transporting the modules, which need to be reconfigured at known positions. In the late 1980s, the connection mechanism was first introduced into cellular robotic systems (CEBOT) to realize the docking of different modules [22]. Fukuda studied a docking system for a cell-structured robot using a hook-type coupling mechanism, in which the connection mechanism requires a very precise alignment. Rubenstein et al. demonstrated that the CONRO robot can realize docking within some distance and angle misalignment [23]. Castano et al. described a robotic module developed in the framework of the CONRO project; the robots can reconfigure into different modules [24]. Stoy et al. used the ATRON self-reconfigurable robot to demonstrate that 2 three-module robots can dock and merge into a large robot [25]. Murata et al. proposed a docking method for a selfreconfigurable modular robot (M-TRAN), which is based on simple visual feedback by using an additional camera module and LED transmitters equipped on the M-TRAN modules [26].

C. Self-Assembly Robots Self-assembly is a concept offering a new approach for robot design. It means that the robot modules are able to assemble into a connected structure, and inversely, a robotic structure can also disassemble into a group of unconnected units. Groß and Dorigo gave a detailed review on self-assembly in the robotic field [4]. Docking between multiple mobile units is really a challenge. The docking mechanism should have the functions of positioning, guiding, and sensing, and it must overcome the relative misalignment between two robots when they move to the position for docking. A reliable docking between two robots depends on the guiding of the docking mechanism. Delrobaei and McIsaac have recently demonstrated that two autonomous moving robots successfully docked within certain misalignment, but this study only focused on the design of docking mechanism and did not touch upon the perceptive guiding system [27]. Wong et al. proposed a docking method based on the neural-network control and guidance, and achieved active docking between two autonomic robots [28]. Swarm robots with the functions of self-assembly and selfreconfiguration are similar to the mobile self-reconfigurable robots, i.e., each individual robot has its autonomous mobility and multiple robots can be integrated into a new robot by connection. The proposed self-assembly robots include Millibot [29], s-bot [6], [21], [30], etc. All these robots are composed of individual robots with homogeneous and heterogeneous units and can achieve autonomous connection between two or more individual units.

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. WEI et al.: SAMBOT: A SELF-ASSEMBLY MODULAR ROBOT SYSTEM

3

III. DESIGN OF THE MECHANICAL AND ELECTRICAL SYSTEM A. Design Requirements The Sambot is a multirobot system, which has synthesized the advantages of both self-reconfigurable robots and selfassembly robots. Each Sambot is a completely autonomous mobile robot, similar to the individual robot in swarm robots. Through self-assembly, multiple Sambots can form a robotic structure, such as a snake-like structure or a quadruped structure. This kind of robotic structure has both the self-reconfiguration and locomotion abilities similar to those of the chain-type selfreconfigurable robots. In order to realize these functions, Sambot must meet the following design requirements. 1) Autonomous mobility: Sambot should be an autonomous mobile robot, whose mobile mechanism can be wheels or tracks. Every robot contains in itself the power supply, microcontroller, actuators, sensors, and communication units. 2) Self-assembly: Sambot should have an active docking mechanism, so that it can realize autonomous connection and separation. Different from the docking mechanism of the existing self-reconfigurable robot, Sambot should have the ability of long-distance docking similar to that of the autonomous mobile robot. They can approach each other under the guidance of sensors and overcome the misalignment between two robots. 3) Locomotion: The robotic structure formed through selfassembly of multiple Sambots should have the locomotion capability of chain-type self-reconfigurable robots. This requires two or multiple Sambots to have relative mobility after docking. Therefore, its shape should be a cube or cuboid. 4) Self-reconfiguration: The robotic structures assembled by multiple Sambots should have the ability of selfreconfiguration. They can transform from one robotic structure (e.g., a snake-like robot) into another (e.g., a quadruped robot). B. Mechanical Design From these requirements, it is found that the mechanical design of Sambot is really a challenging task. Besides the aforementioned functional requirements, Sambot must be compact, containing in itself all the stand-alone parts of mechanism, actuator, controller, sensor, communication unit, and power supply. Then, the robotic structures composed by Sambots can have excellent abilities of locomotion and reconfiguration. As shown in Fig. 1, the structure of Sambot includes an active docking interface and an autonomous mobile body. Fig. 2 gives the exploded view of Sambot, demonstrating the connection of the parts. On the active docking interface, there is a pair of active docking hooks, which can dock with any pair of docking grooves in the front, back, left, or right passive docking interface on the autonomous mobile body of another Sambot. The mechanical design of the docking hooks and docking grooves allows two Sambots to realize autonomous docking within some misalignment. The docking touch switch and docking infrared

Fig. 1. Photographs of Sambot (overall size is 80 mm × 80 mm × 102 mm). (a) 3-D view. (b) Front view. (c) Side view. (d) Top view. (e) Bottom view.

Fig. 2.

Exploded view of the mechanical structure of Sambot.

sensors on the active docking interface are used to guide the docking and judge whether the two Sambots are in the state of docking. A pair of detecting infrared sensors are installed on the upper parts of the front and back of the autonomous mobile body, respectively. They are used to detect obstacles in front of the robot. In addition, a pair of approaching infrared sensors are also installed on the lower parts of the front, back, left, and right sides of the autonomous mobile body, respectively. By reacting to the docking sensors on the active docking interface of other Sambots, the approaching infrared sensors monitor the relative positions of the two Sambots and provide navigating information for the docking. As shown in Fig. 1(b), the active docking interface of Sambot can rotate around the central axis in a range of ±150◦ . During the docking process, the interface of the active docking robot rotates 90◦ forward or backward. The active docking interface can, therefore, dock with the passive docking interface of another Sambot. Once the docking is accomplished, the rotating joint can rotate around the central axis to achieve locomotion of the robotic structure. As shown in Fig. 1(c), there is a pair of grooves on the front, back, left, and right sides of the main body, respectively. During docking, the hooks can completely insert into the grooves of another Sambot, realizing seamless connection between two Sambots. After docking, the six electric touch points on the active interface are pressed tightly and fit with the six electric



Fig. 3.

Autonomous docking of two Sambots.

Fig. 4.

Mechanism of the docking hooks.

touch points on the passive interface. These electric touch points are used for the control area network (CAN) bus communication and charging between Sambots. The main body is driven by two symmetrically distributed wheels on the bottom. As shown in Fig. 1(e), a pair of spring flakes are installed on the bottom to ensure smooth motion. The autonomous docking between two Sambots is the basis to achieve the self-assembly of multiple Sambots. As shown in Fig. 3, the autonomous docking includes four phases, namely, seeking, guiding (navigating), docking, and locking. C. Docking Mechanism Besides the functions of long-distance guiding and misalignment adjusting, the docking mechanism must have the ability of fast and reliable connection and high-structural strength. Specifically, it should meet the following requirements: 1) it can detect other robots, and within certain distance realize the positioning and guiding of two robots; 2) it can realize docking within a certain range of misalignment; 3) after docking, the gap between the two robot modules should be as small as possible, because the gap would decrease the moment of torsion during locomotion; 4) the structural strength should be high enough to avoid damages during and after connection; 5) the connection and separation should be fast; 6) the connection should be reliable; and 7) it should have the function of mechanical self-lock, which do not rely on the torque of the motor, and thus, can keep the energy consumption at the lowest level. The docking hook mechanism of Sambot is driven by worm gears. It only occupies a small space and can achieve zero distance for separation. As shown in Fig. 4, the inside driven mechanism is as follows: the output of a micro dc motor is decelerated by a pair of gears, and then, transmitted to the turning shaft; the ends of the turning shaft are connected to worm gears, which drive the hooks to rotate, realizing connection, and separation. As shown in Fig. 2, the micro dc motor and the whole dock-

Fig. 5.

Arrangement of docking grooves.

Fig. 6.

Force analysis of the docking hooks.

ing mechanism are embedded in the active docking interface. Power supply of the micro dc motor comes from the battery in the autonomous mobile body through an electric wire. To ensure the reliability and flexibility of the connection, the design of the hooks and grooves is optimized as the following four steps. 1) The docking grooves are asymmetrically distributed, allowing synchronized docking on the front, back, left, and right sides without interference. As shown in Fig. 5, Sambots A and B are docked by hook 1 (the bold lines show the contact sides of modules A and B). Now, assume that module C also needs to be docked with module B by hook 2. To avoid interference, when hook 2 rotates into the groove of module B, the grooves on the active docking interface of Sambot A keep open, thus realizing the synchronized docking on the front, back, left, and right sides without interference. 2) The contour line of the docking hooks is designed as the involute of a circle, which makes the hooks bear equal force during docking. During docking, the hooks rotate into the grooves. When the hooks bear force, the two Sambots are pulled to approach each other. It is required that the radial load on the rotating shaft of the hooks should be constant. As shown in Fig. 6, to analyze the force beared by the hooks during docking, a curve is used to describe the shape of the internal side of the hook. Under the action of the same torque, the hooks should transmit constant radial force to the shaft. If the hook’s torque is M , then the tangential force at an arbitrary point is as follows: F =

M . R

(1)


5

Fig. 7. Force bearing analysis of the hook root after two Sambot are docked and locked. (a) Before optimization. (b) After trioptimization.

The radial force is as follows: M cot α. (2) F1 = R Suppose that the initial angle is α0 = π/4, then the initial radial force that the hook bears is as follows: M F0 = cot π/4. (3) R0 During the locking process, the hook is subjected to constant radial force, therefore, F 1 = F0

(4)

cot α cot π/4 = R R0

(5)

dR = dΦ · R · sin α.

(6)

because

Then, the curve equation of the hook contour is as follows (described in polar coordinates): 2 ϕ2 R R0 1 1+ dR = dΦ. (7) R ϕ1 R 0 R0 3) The contact surface between the hook and groove is smooth, slight sliding might occur after docking. Therefore, we design a lock hole at the root of the hook to eliminate the radial load applied by the docking hook shaft after two robots are locked. Sheer load between the two modules is slight in most cases except when the modules are carried laterally. However, in this case, both force and torque are applied to the hooks and worm gears that are designed exactly. After the two Sambots are locked, the force applied by the hook is shown in Fig. 7(a). F 1 is the resistance given to the hook by the groove surface, F 2 is the pulling force applied by the hook shaft, and M is the torque exerted by the hook. When two Sambots are docked and locked, if F 1 and F 2 are not along the same straight line, then the torsion moment applied by the hook is as follows: M = F1 · d

(8)

where d is the distance between F 1 and F 2 . As shown in Fig. 7(b), the shape of the hook root is optimized, so that F 1 and F 2 are along the same straight line. Therefore, the hook bears no torsion moment when

Fig. 8.

Misalignment during docking of two Sambots.

TABLE I PERMISSIBLE MISALIGNMENT DURING DOCKING BETWEEN TWO SAMBOTS

two Sambots are docked firmly. Then, the self-lock of the two Sambots is also realized. After docking, the driving motor of the worm gears can be switched OFF to reduce energy consumption. 4) The docking hook is in a curved-pyramid shape, which can enable the two Sambots to dock within a certain range of misalignment. As shown in Fig. 8, the hook tapers in size from its root to the end tip. Therefore, when the two Sambots have a certain misalignment, the hooks can still dock reliably with the grooves of the other Sambot. Obviously, such mechanical design of the hook can effectively increase the success rate of autonomous docking. The 3-D misalignment is allowed within the ranges shown in Table I. D. Electronic System The electronic system of Sambot can be divided into three parts: the main control unit, the sensor and actuator unit, and the communication unit, as shown in Fig. 9. 1) Main Control Unit: This unit uses a STM32 microprocessor of the ARM series as the main processor. The STM32 controls the robot’s motion, positioning, and other higher level decision-making tasks. This unit can collect information from the gyroscope and accelerometer. It receives the encoder information via I2 C interface, and the result can be used to control navigation. The main control board periodically collects information from each sensor via I2 C interface and runs the control algorithm. At the same time, this unit can obtain information from other robots through the global communication unit, allowing it to make task decision by referring to the global behavior. 2) Sensor and Actuator Unit: In Sambot, there are four micro dc motors, which control the left and right wheels, the active docking interface and the docking hook, respectively. Each motor is controlled by a separate ATMega8 microcontroller, which meanwhile also collect information from the encoder and



Fig. 9.

Structural diagram of Sambot’s electronic system.

sensor. The STM32 is connected to these ATMega8 s through an I2 C serial communication pattern named “one master and four slavers.” ATMega8 returns the sensor information according to the commands from the master, and executes the corresponding motor control instruction. 3) Communication Unit: Sambot’s communication unit is divided into two parts: ZigBee wireless communication in the swarm state and CAN bus communication in the robotic structure state. The ZigBee communication uses TI’s CC2430 chip and C51 microcontroller core in the underlying protocol stack layer and the upper layer. CC2430 is connected to STM32 by a serial interface. The CAN bus communication uses VP230 as CAN transceiver to connect with the CAN interface in STM32. When multiple Sambots form a robotic structure, they are also connected to one another by CAN interface. Therefore, the Sambots in a robotic structure can obtain the control information and the state signals of other Sambots, and then, make corresponding decisions. IV. CONTROL ALGORITHM AND SOFTWARE ARCHITECTURE This section introduces the control algorithm of Sambot. The behavior-based control is adopted here [31]. The motor scheme is established for self-assembly tasks of two or more Sambots. The basic behaviors such as target-searching and active docking are also established. The target searching behavior enables Sambots to detect the target robot by the infrared sensors, and then, move to the docking position. The active docking behavior enables Sambot to autonomously dock with the target robot under the guidance of the docking infrared sensors. This section also discusses the formation of a robotic structure composed of multiple Sambots, the overall configuration, and the control of motion. The distributed gait control schemes are set up to achieve the locomotion and control of a robotic structure. A. Motor Scheme of Sambot As an autonomous mobile robot, Sambot has the abilities of computing, local perception, and communication. It also has the following limitations.

1) No Sambot has global coordinate signals. 2) Every Sambot has only the local perception ability. Here, a Sambot can detect objectives through the detecting infrared sensors, and perform navigation by the approaching infrared sensors. 3) Each Sambot has only the local communication, i.e., it uses the infrared communication. (Although Sambot has the ability of ZigBee global wireless communication, we do not use it here.) Here, Sambot adopts the behavior-based control method, i.e., the controller is composed of a series of behaviors and each behavior is used to realize a specific function. Every behavior combines a series of motor schemes. Sambot has established the following basic motor schemes. 1) Collisions avoidance: This motor scheme acts in accordance with the detecting infrared sensors to avoid obstacles. Specifically, as soon as the information of an obstacle is transmitted into Sambot’s detecting infrared sensors, Sambot immediately stops its current forward-moving behavior, retreats back, turns to another random direction and moves forward again. 2) Self-rotation: It rotates at angle velocity ω. The selfrotation angle Φ ∈ (−180◦ , 180◦ ) and its specific value is determined according to the left and right wheels driving motor encoder signal and the electronic compass of Sambot. 3) Forward/backward motion: Sambot can move forward or backward for a distance L (L ≥ 0) at velocity v and this movement is realized through motor and encoder closedloop control. 4) Forward arc At velocity v and having the current position as the starting point, Sambot can move forward along a circular arc of central angle ψ∈(−180◦ , 180◦ ) and of radius R. 5) Dockboard rotate: The active docking interface rotates at angle velocity ω for an angle ∈ (−180◦ , 180◦ ). This action can be used to control the whole motion of the robotic structure after self-assembly. 6) Alignment: Sambots can adjust their moving direction during the docking process. When Sambots move forward at low speed, the two approach infrared sensors collect information of orientation for the purpose of alignment. 7) Locking: When the two docking infrared sensors and the mechanical touch switch are triggered at the same time, they control the docking hook, drive the motor and execute the locking action. 8) Unlocking: The docking hooks may be opened to separate the two robots. When the mechanical touch switch restores to its initial state, the unlocking operation is accomplished. Sambot uses the infrared sensors to detect its surrounding environment, and then, responds to the behaviors of the robots. There are five kinds of sensors with different functions. 1) Detecting infrared sensors (range: 0–160 mm): There are two pairs of detecting sensors in the upper sides of the front and back interfaces, respectively, as shown in Fig. 2. They are used to detect other Sambots or obstacles.


7

2) Approaching infrared sensors (range: 0–150 mm): There are two pairs of approaching sensors in the lower sides of the front, back, left, and right interfaces, respectively. They provide navigation signals for the self-assembly. 3) Docking infrared sensors (range: 0–150 mm): There are two pairs of docking sensors in the lower and upper sides of the active docking interface, respectively. They guide the autonomous docking process. 4) Mechanical touch switch: The switch has two values, “1” stands for “press-down”, while “0” denotes no action. 5) Electronic compass sensor: It uses an angle β ∈ (0◦ –360◦ ) to represent the current orientation of Sambot.

B. Target-Searching Behavior Target-searching is one of the most basic behaviors of swarm robot. For example, in the process of autonomous docking, a Sambot has to find the target Sambot first, then navigate to the docking position, and finally, complete the docking via a series of actions. Similarly, target-searching is also a key step for swarm robots to execute their tasks including gathering, following, formation collecting, and coordinate control. Assume that we need to dock two Sambot autonomously in an enclosed environment with curbs. The docked Sambots are called the target, which keeps its position and orientation fixed during the whole process of subsequent docking. According to the requirement of a docking task, the target opens its approach infrared sensors (i.e., emitters, which give the docking direction) and waits for another Sambot to dock with it. The docking Sambot is called the active-SA, which has random orientation and distance initially. The active-SA needs to wander about to find its target first, then navigates around the target to find the docking direction, and finally, docks with the target. All these behaviors rely on the perception abilities of the detecting infrared sensors and approaching infrared sensors. The detecting sensor perceives the object in front of it by the infrared reflection and its perception range is 0 – 160 mm. Based on the motor scheme of self-rotation, the orientation of the target relative to active-SA can be determined. The approaching infrared sensor perceives the docking direction by infrared reflection with the approach infrared sensors (emitters) of the target and its perception range is 0 – 150 mm. It is used to search for the docking direction and provides guidance for the docking. Target-searching includes two subbehaviors: wandering and navigation. 1) Wandering: The front detecting infrared sensors are turned on first, and then, the active-SA wanders in a random path on the experiment table. Each edge of the experiment table is 40 mm (higher than the approaching infrared sensors and lower than the detecting infrared sensors). As the robot wanders to the edge of the experiment table, the approaching infrared sensor can detect it. Then, the robot rotates randomly and goes backward until the front detecting infrared sensors have input signal, which means a target has been found. After this, the active-SA switches to the navigation behavior.

Fig. 10.

Schematic diagram of the navigation algorithm.

2) Navigation: During navigation, the active-SA goes anticlockwise around the target until it finds the docking direction. This process is guided by infrared signals. The infrared-based guiding idea is shown in Fig. 10. The active-SA first adjusts its orientation to align itself with the target (the orientation of the target is predetermined). Then, it self-rotates and records its location angle α relative to the target. Because the longest detecting radius of the detecting infrared sensor is 200 mm (i.e., 160 mm plus 40 mm of half a robot’s body length), the coordinates (xi , yi ) of point C can be calculated by referring to Fig. 10. Then, the active-SA can align with the target by the following steps: 1) the active-SA moves in the direction of X to the location of xi plus 1.5 l (here, l is approximately the body length of the Sambot 80 mm, and this location is in the sensitive range of the docking infrared sensor); 2) it turns 90◦ ant-clockwise; 3) it moves a yi + 1.5 l distance in the direction of Y -axis. An anticlockwise circling around the target will be accomplished. During moving, the approaching infrared sensor in the active-SA is always turned ON and aligned with the target. The active-SA moves on until the sensor receives signal, which means that the docking direction has been found. Then, the navigation behavior ends. C. Active Docking Behavior The active docking behavior includes two subbehaviors: docking and locking. 1) Docking: At first, the active-SA needs to turn ON the docking infrared sensors (receivers) on the active docking interface. According to the signal from the approaching infrared sensors of the target, the active-SA adjusts its



own position and goes toward the target. Usually, there are three situations: the first is that the docking infrared sensors on both the right and left sides of the active-SA receive signals at the same time. It means that the activeSA has aligned with the target. The active-SA can move forward on with the prerequisite that its right and left approaching infrared sensors always have signal input. It stops moving when the mechanical touch switch on the docking interface is pressed down. Then, the locking behavior will take place. The second situation is that the right-side docking infrared sensor (receiver) of the activeSA has signal input, but the left-side sensor does not have. This means that the target is at the right side of the activeSA. Therefore, the active-SA moves 60 mm (the distance between the two docking infrared sensors) to the right and aligns its position right and left in the proximity until both docking infrared sensors (receivers) have signal input. The third situation is that the left-side docking infrared sensor (receiver) of the active-SA has signal input, whereas that on the right does not have. This means the target is at the left side of the active-SA. Therefore, the active-SA moves 60 mm to the left and aligns its position right and left in the proximity until both docking infrared sensors (receiver) have signal input. It deserves noting that here we only described the function of docking one unit to a single stationary unit or a stationary robotic structure. This provides a basic technique for the docking of multiple units to autonomously create a large complex structure. If a group of Sambots are to dock one another autonomously to form a complex robotic configuration, we need to select a Sambot as SEED and other Sambots as docking robots. The docking robots adopt a behavior-based controller to achieve self-assembly with the SEED. The SEED decides the configuration growth way of the robotic structure. 2) Locking: The locking behavior is relatively simple. The docking hooks can accomplish it by locking tightly. Here, the electric touch points of both the active-SA and target contact each other and send handshaking signal to affirm the completion of CAN bus communication connection. Afterward, the active-SA sends basic information about itself such as ID to the target. After the active-SA confirms the connection with the target, the locking is accomplished. D. Locomotion After the docking task is finished, the robotic structure composed of multiple Sambots is formed. Such a robotic structure has a high ability of locomotion. When multiple Sambots are connected, the two double-wheel driving motors stop working, and only the rotation driving motor on the active docking interface provides a rotation degree of freedom. This is similar to the cases of most chain-type self-reconfigurable robots. As shown in Fig. 11, the Sambot in a robotic structure is equivalent to a two-link module with one degree of freedom. The central circle stands for the rotation center, which is, in

Fig. 11.

Simplified configuration of Sambot.

Fig. 12.

Configuration of robotic structures assembled by multiple Sambots.

Fig. 13.

Analysis of caterpillar’s sinusoidal wave motion.

fact, the center of the main body. The white link represents the main body and its length is 40 mm, half of that of the main body. The black link denotes the active docking interface, whose length is 62 mm, i.e., 40 mm plus the thickness of the docking interface. As shown in Fig. 12, the robotic structure composed of multiple Sambots may have many different configurations such as line (snake or caterpillar), ring, triangle (tripod), orthogon (quadruped), parallel (quadruped or six-limbed), etc. Here, let us consider the locomotion of a caterpillar assembled by five Sambots, as shown in Fig. 13. The nodes S1, S2, S3, S4, and S5 stand for the five Sambots, respectively. Table II gives the gait control scheme of a sinusoidal wave motion for a caterpillar [32]. The maximum rotation angle is 30◦ and the anticlockwise rotation is taken as positive. As shown in Fig. 13, the sinusoidal


9

TABLE II GAIT CONTROL TABLE OF A CATERPILLAR’S SINUSOIDAL WAVE FORWARD MOTION

Fig. 14. Autonomous docking of two Sambots within the range of infrared perception.

wave motion of the caterpillar configuration can be divided into two phases. 1) The phase when sinusoidal wave is generated, i.e., from Step 0 to Step 1. At Step 0, the rotating angle of all modules are 0, and the caterpillar is waiting for the beginning of locomotion. At Step 1, modules S1 and S4 rotate 30◦ , modules S2 and S3 rotate –30◦ , and a sinusoidal wave is then produced. Meanwhile, the caterpillar moves forward a step Δx. 2) The phase when sinusoidal wave is transmitted successively, e.g., from Step 2 to Step 5. This procedure can be repeated again and again, enabling the robot to move forward continuously. The distributed CAN bus control method is applied in the caterpillar. Sambot S1 acts as the main control robot and other Sambots (S2–S5) are subordinate robots. The gait control table is saved in the main control robot. The main control robot S1 sends the gait and delay time to S2–S5 successively. The control algorithm of the caterpillar is shown in the Appendix. Here, we only use the caterpillar as an example to show the feasibility of the aforementioned gait control method. As for other configurations, self-adaptive algorithms may be adopted in the gait control, which is a significant problem in the future work.

V. EXPERIMENTS This section introduces the autonomous docking experiments of Sambots and the locomotion experiments of robotic structures. The autonomous docking experiments are performed in two cases. In the first case, the target Sambot is in the infrared perception range of the active-SA. The active-SA rotates around itself to find the target through its detecting infrared sensors, and then dock, with it. In the second case, the docking task is more difficult. The target Sambot is located at the center of an experimental platform of the size 600 mm × 600 mm. The active-SA is put randomly at a corner of the platform. It is shown that the active-SA finds the target while wandering around, then navigates itself to the docking direction, and finally, completes the autonomous docking. This kind of docking is referred to as directional autonomous docking. Additionally, the self-assembly experiment on a complex quadruped configuration are also implemented.

Fig. 15.

Directional autonomous docking experiment of two Sambots.

A. Autonomous Docking Within the Range of Infrared The emphasis of this experiment is to test and verify the navigation guiding function of the infrared sensors and the docking function of the active docking hooks. The experiment adopts a simple docking tactic. As shown in Fig. 14, first of all, the active-SA rotates at its initial position [see Fig. 14(a) and (b)], searching for a target in its vicinity by the detecting infrared sensor. Then, we place a target at the position of 150 mm away from the right side of the active-SA [see Fig. 14(c)]. Soon, the active-SA finds the target with the help of the detecting infrared sensor [see Fig. 14(d)]. At once, it begins to move toward the target under the guidance of the docking infrared sensors [see Fig. 14(e)]. When they contact [see Fig. 14(f)], the mechanical touch switch on the active docking interface of the active-SA is pressed down, and then, the active docking hooks of the activeSA are opened [see Fig. 14(g)]. Finally, the active-SA inserts its docking hooks into the grooves of the target and locks the target tightly [see Fig. 14(h)]. B. Directional Autonomous Docking All the experiments have been done on a 600 mm × 600 mm platform. In each experiment, the target Sambot is located at the center of the platform and the active-SA is initially placed at any corner. The process of directional autonomous docking is shown in Fig. 15, where the red arrow points to the docking direction of the target Sambot. For the convenience of description, let us label the left-front, right-front, left-back, and right-back corners of the platform by 1, 2, 3, and 4, respectively. It deserves noting that the directions of left, right, front, and back are defined relative to the target Sambot, which is always fixed at the platform center. As stated earlier, in each experiment, the active-SA is initially placed at any corner. Therefore, its initial position may be denoted by 1, 2, 3, or 4. Additionally, at each initial position four



TABLE III EXPERIMENTAL DATA OF DIRECTIONAL AUTONOMOUS DOCKING

Fig. 16.

random initial orientations are tried for the active-SA. Therefore, 16 experiments have been done in total. Table III gives all the experimental results and records the time for wandering, navigation, and active docking in every case, respectively. In all the 16 experiments, only one failed. In this failure case, at the final moment of docking, there was some misalignment between active-SA and the target. The mechanical touch switch on the active docking interface was not pressed down. Therefore, the docking hooks did not execute the locking behavior, which led to the failure. From Table III, it is found that the wandering time varies remarkably as the initial position and/or orientation of the activeSA changes, and so does the navigation time. The longest wandering time was 55.4 s (see the Experiment 7), while the shortest was merely 2.8 s (see the Experiment 7). The longest time of navigation was 88.4 s (see the Experiment 12), but the shortest was only 0.7 s (see the Experiment 6). Here, the time variation was really a random phenomenon. It took different time for the active-SA to navigate from different start positions to the docking direction of the target. However, Table III also shows that the time spent for docking only experienced relatively small variations as the initial position and/or orientation of the active-SA changes. The average docking time was 18.1 s. C. Self-Assembly for a Quadruped Configuration As shown in Fig. 16, we conducted the self-assembly experiments for a quadruped configuration on an experimental platform of size 1000 mm × 1000 mm. The SEED is located at the center of the platform and the docking robots are put randomly at the four corners. For the quadruped configuration, the docking robots can dock with SEED from the front, left, right, and back interfaces. The experiment is finished within 170 s. In this self-assembly experiment, all the docking robots execute the same control algorithm, which is independent of the target configuration and other Sambots. D. Caterpillar Locomotion Experiment A locomotion experiment was done on a caterpillar configuration composed of five Sambots. The rotation range of each

Self-assembly experiments for a quadruped configuration.

Fig. 17. Caterpillar locomotion of a robotic structure assembled by five Sambots.

module was 30◦ , and the delay time was 300 ms. As shown in Fig. 17, the wave was generated in Fig. 17(b). From Fig. 17(b) to (f), the wave propagates to push the robot forward continuously. From Fig. 17(b) to (h), the robot moved forward a distance of about 3.4 modules (i.e., approximately 280 mm) in 9 s. Therefore, the actual moving speed of the robotic structure was about 30 mm/s. In conclusion, it is easy to realize the locomotion control of caterpillar or other configurations composed of multiple modules by the distributed CAN bus method, as long as the gait control table for the configuration is established. VI. DISCUSSIONS This section discusses the features of structural design, selfassembly, self-reconfiguration, and locomotion of Sambot. A. Structural Design For a self-reconfigurable robot, the structural design is one of the biggest challenges, especially the design of the docking and locomotion mechanisms. Autonomous motion and limited perception ability are the two main features of the swarm robots. The structural design of Sambot utmostly combined the features of swarm and self-reconfigurable robots. On one hand, it has the


Fig. 18.

Structural comparison between M-TRAN and Sambot.

autonomous moving ability of swarm robots; on the other hand, its autonomous docking and locomotion abilities are as good as those of the existing self-reconfigurable robots. The classical chain-type self-reconfigurable robots (such as M-TRAN [33], [34], PolyBot [35], and SuperBot [36], etc.) are mostly rectangular. Each unit has 2–3 degrees of freedom and 4–6 docking interfaces. For example, M-TRAN has six docking interfaces, three active (masculine) ones and three passive ones (feminine), as shown in Fig. 18. The docking mechanism of Sambot consists of an active docking interface (on which there is a docking hook) and four passive docking interfaces on the front, back, left, and right sides. Structurally speaking, because Sambot has only one active docking interface, it can only assemble into a chain-type reconfigurable robot (while M-TRAN has the features of both the chain- and lattice-type robots). Because Sambot itself is an autonomous mobile robot, it has the abilities of autonomous motion and docking within a certain range, but M-TRAN modules do not have such abilities. B. Stand-Alone Design The stand-alone design is another special feature of Sambot. For most existing self-reconfigurable robots, the radio control (RC) motor is chosen as the driving part of the motor for the convenience of design and control. In spite of these conveniences, the RC motor is large in size, which is a restraint for the design and distribution of the modules. Therefore, the compact standalone modules, such as M-TRAN, generally choose miniature dc servo motor instead of RC motor. For Sambot, we use four dc motors with decelerator and encoder and adds a rotating potentiometer onto the active docking interface driving motor. This helps to realize the double closedloop feedback control of position, which is very important for the locomotion control of a robotic structure composed of multiple Sambots. Additionally, in order to make the best use of the inner space, modular method is also applied to design the inside control circuit board. C. Autonomous Docking For the existing self-reconfigurable robots, the autonomous docking often depends on the coordination between modules. However, the docking of Sambot is, in fact, the autonomous docking of two mobile robots. At present, most researchers use high-performance sensors, such as cameras and laser range finders to achieve the docking between two mobile robots. The

11

Fig. 19. Coordinated transport of a straight-line configuration composed of five Sambots. (a) Initial state. (b) Lifting up one module. (c) Lifting up two modules. (d) Arrive in position.

s-bot platform [6], [30], for example, combined cameras and LED rings together to control the positioning and navigation between two robots. Sambot only relies on the limited perception ability of infrared sensors to realize the autonomous docking between two robots, which includes the necessary phases of target searching, navigation, and docking. D. Self-Reconfiguration and Load Bearing A robotic structure composed of multiple Sambots can transform from one configuration to another by autonomous connection and separation between modules. Just like other reconfigurable robots, Sambot can also transform into different configurations through relative motion between modules. During the process of self-reconfiguration, the rotating mechanism must get enough torque to lift other modules. The torque bearing capacity of a single module is 1.5 N·m. Fig. 19 shows the reconfiguration process of a straight-line robotic structure composed of five Sambots. Obviously, it can realize self-reconfiguration by lifting up one and two modules. The ability of self-reconfiguration through coordinated transport of modules provides Sambot with a new function. For example, a line configuration composed of six Sambots can form a closed ring to roll on the platform. In addition, this function may enable the line configuration to lift itself and stride across an obstacle. VII. CONCLUSION AND FUTURE WORK This paper presents a novel design of a Sambot, which itself is an autonomous mobile robot with the functions of both selfassembly and self-reconfiguration. The structural design, electronic design, and control algorithms of Sambot are described in detail. We also did some experiments to demonstrate the autonomous docking between two Sambots and the locomotion of a robotic structure composed of multiple Sambots. This paper has laid down a good foundation for further investigations on robotic structure systems, whose configurations and functions can evolve. Future research is planned to further improve Sambot and the associated robotic structure systems. The first one is to improve the control algorithms of the self-assembly of multiple Sambots. For example, various intelligent control methods may be tried to realize self-assembly and self-reconfiguration. The second is to optimize the motion control of the robotic structure composed of multiple Sambots. On the basis of the existing standard gait control table, a self-adaptive motion control (such as central



pattern generator (CPG) control) can be adopted to improve the motion performance of the robotic structure. Finally, in order to design an advanced robotic structure, whose configuration and function can both evolve in varying environments, the dynamic coupling between the robotic structure system and the outside environment should also be studied.

3) Control algorithm of S1 for caterpillar movement

APPENDIX The navigation algorithm and the active docking algorithm presented in Section IV-B and C, and the control algorithm of the caterpillar movement presented in Section IV-D are included. 1) Navigation algorithm

REFERENCES

2) Active docking algorithm

[1] E. S¸ahin, S. Girgin, L. Bayindir, and A. E. Turgut, “Swarm robotics, swarm intelligence: Introduction and applications,” in Natural Computing Series, Berlin, Germany: Springer, 2008, pp. 87–100. [2] Anderson, G. Theraulaz, and J. Deneubourg, “Self-assemblages in insect societies,” InsectesSociaux [Insects Soc.], vol. 49, no. 2, pp. 99–110, 2002. [3] G. M. Whitesides and B. Grzybowski, “Self-assembly at all scales,” Science, vol. 295, no. 5564, pp. 2418–2421, Mar. 2002. [4] R. Groß and M. Dorigo, “Self-assembly at the macroscopic scale,” Proc. IEEE, vol. 96, no. 9, pp. 1490–1508, Sep. 2008. [5] R. Pfeifer, M. Lungarella, and F. Iida, “Self-organization, embodiment, and biologically inspired robotics,” Science, vol. 318, no. 5853, pp. 1088– 1093, Nov. 2007. [6] R. Groß, M. Bonani, F. Mondada, and M. Dorigo, “Autonomous selfassembly in swarm-bots,” IEEE Trans. Robot., vol. 22, no. 6, pp. 1115– 1130, Dec. 2006. [7] M. Yim, W. -M. Shen, B. Salemi, D. Rus, M. Moll, H. Lipson, E. Klavins, and G. S. Chirikjian, “Modular self-reconfigurable robot systems,” IEEE Robot. Autom. Mag., vol. 14, no. 1, pp. 43–52, Mar. 2007. [8] S. Kornienko, O. Kornienko, A. Nagarathinam, and P. Levi, “From real robot swarm to evolutionary multi-robot organism,” in Proc. 2007 IEEE Evol. Comput., Sep. 25–28, 2007, pp. 1483–1490. [9] G. Beni, “From swarm intelligence to swarm robotics,” in Lecture Notes in Computer Science, Berlin, Germany: Springer-Verlag, 2005, pp. 1–9. [10] G. Caprari and R. Siegwart, “Mobile micro-robots ready to use: Alice,” in Proc. IEEE RSJ Int. Conf. Intell. Robots Syst., 2005, pp. 3295–3300. [11] M. Cianci, X. Raemy, J. Pugh, and A. Martinoli, “Communication in a swarm of miniature robots: The e-Puck as an educational tool for swarm robotics,” in Proc. 2nd Int. Workshop Swarm Robot. vol. 4433, (Lecture Notes in Computer Science), Springer, 2007, pp. 103–115. [12] X. Shen, J. Dumpert, and S. Farritor, “Design and control of robotic highway safety markers,” IEEE/ASME Trans. Mechatronics, vol. 10, no. 5, pp. 513–520, Oct. 2005. [13] C. P. Tang, R. M. Bhatt, M. Abou-Samah, and V. Krovi, “Screw-theoretic analysis framework for cooperative payload transport by mobile manipulator collectives,” IEEE/ASME Trans. Mechatronics, vol. 11, no. 2, pp. 169–178, Apr. 2006. [14] J. Pugh, X. Raemy, C. Favre, R. Falconi, and A. Martinoli, “A fast onboard relative positioning module for multirobot systems,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 151–162, Apr. 2009. [15] A. Franchi, L. Freda, G. Oriolo, and M. Vendittelli, “The sensor-based random graph method for cooperative robot exploration,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 163–175, Apr. 2009. [16] S. S. -Talay, T. R. Balch, and N. Erdogan, “Multiple traveling robot problem: A solution based on dynamic task selection and robust execution,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 198–206, Apr. 2009. [17] A. Viguria and A. M. Howard, “An integrated approach for achieving multirobot task formations,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 176–186, Apr. 2009. [18] C. A. Kitts and I. Mas, “Cluster space specification and control of mobile multirobot systems,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 207–218, Apr. 2009.


[19] S. Khoo, L. Xie, and Z. Man, “Robust finite-time consensus tracking algorithm for multirobot systems,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 219–228, Apr. 2009. [20] J. Takahashi, T. Yamaguchi, K. Sekiyama, and T. Fukuda, “Communication timing control and topology reconfiguration of a sink-free meshed sensor network with mobile robots,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 2, pp. 187–197, Apr. 2009. [21] E. Tuci, R. Groß, V. Trianni, F. Mondada, M. Bonani, and M. Dorigo, “Cooperation through self-assembly in multi-robot,” ACM Trans. Autonom. Adapt. Syst., vol. 1, no. 2, pp. 115–150, 2006. [22] T. Fukuda and S. Nakagawa, “Method of autonomous approach, docking and detaching between cells for dynamically reconfigurable robotic system cebot,” JSME Int. J., vol. 33, no. 2, pp. 263–268, 1990. [23] M. Rubenstein, K. Payne, P. Will, and W. Shen, “Docking among independent and autonomous CONRO self-reconfigurable robots,,” in Proc. IEEE Int. Conf. Robot. Autom., Apr. 2004, vol. 3, pp. 2877–2882. [24] A. Castano, A. Behar, and P. M. Will, “The CONRO modules for reconfigurable robots,” IEEE/ASME Trans. Mechatronics, vol. 7, no. 4, pp. 403–409, Dec. 2002. [25] K. Stoy, D. J. Christensen, D. Brandt, M. Bordignon, and U. P. Schultz, “Exploit morphology to simplify docking of self-reconfigurable robots,” in Distributed Autonomous Robotic Systems 8, Berlin/Heidelberg, Germany: Springer, 2009, pp. 441–452. [26] S. Murata, K. Kakomura, and H. Kurokawa, “Toward a scalable modular robotic system: Navigation, docking, and integration of M-TRAN,” IEEE Robot. Autom. Mag., vol. 14, no. 4, pp. 56–63, Dec. 2007. [27] M. Delrobaei and K. A. McIsaac, “Connection mechanism for autonomous self-assembly in mobile robots,” IEEE Trans. Robot., vol. 25, no. 6, pp. 1413–1419, Dec. 2009. [28] J. Wong, G. Nejat, R. Fenton, and B. Benhabib, “A neural-network approach to high-precision docking of autonomous vehicles/platforms,” Robotica, vol. 25, no. 4, pp. 479–492, 2007. [29] B. Brown, J. M. V. Weghe, C. A. Bererton, and P. K. Khasla, “Millibot trains for enhanced mobility,” IEEE/ASME Trans. Mechatronics, vol. 7, no. 4, pp. 452–461, Dec. 2002. [30] R. O’Grady, A. L. Christensen, and M. Dorigo, “SWARMORPH: Multirobot morphogenesis using directional self-assembly,” IEEE Trans. Robot., vol. 25, no. 3, pp. 738–743, Jun. 2009. [31] T. Balch and R. C. Arkin, “Behavior-based formation control for multirobotteams,” IEEE Trans. Robot. Automat., vol. 14, no. 6, pp. 926–939, Dec. 1998. [32] M. Yim, “locomotion with a unit-modular reconfigurable robot,” Ph.D. dissertation, Dep. Mech. Eng., Stanford Univ., Stanford, CA, 1994. [33] A. Kamimura, H. Kurokawa, E. Yoshida, S. Murata, K. Tomita, and S. Kokaji, “Automatic locomotion design and experiments for a Modular robotic system,” IEEE/ASME Trans. Mechatronics, vol. 10, no. 3, pp. 314–325, Jun. 2005. [34] H. Kurokawa, K Tomita, A. Kamimura, S. Kokaji, T. Hasuo, and S. Murata, “Distributed self-reconfiguration of M-TRAN III modular robotic system,” Int. J. Robot. Res., vol. 27, no. 3–4, pp. 373–386, 2008. [35] M. Yim, Y. Zhang, K. Roufas, D. Duff, and C. Eldershaw, “Connecting and disconnecting for chain self-reconfiguration with PolyBot,” Mechatronics, IEEE/ASME Trans. Mechatronics, vol. 7, no. 4, pp. 442–451, Dec. 2002. [36] W.-M. Shen, B. Salemi, M. Moll, M. Rubenstein, H. C. H. Chiu, J. Everist, F. Hou, and N. Ranasinghe, “Multifunctional behaviors of reconfigurable superbot robots,” in Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., 2007, pp. 2548–2548. [37] H. Wei, Y. Cai, H. Li, D. Li, and T. Wang, “Sambot: A self-assembly modular robot for swarm robot,” in Proc. IEEE Int. Conf. Robot. Autom., May 2010, pp. 66–71.

13

Hongxing Wei (M’08) was born in the Inner Mongolia autonomous region, China, in 1974. He received the Ph.D. degree from the College of Automation, Harbin Engineering University, Harbin, China, in 2001. Since 2004, he has been an Associate Professor in the School of Mechanical Engineering and Automation, Beihang University (formerly Beijing University of Aeronautics and Astronautics), Beijing, China. His current research interests include self-assembly swarm robots, modular robotics architecture, mobile sensor networks, and embedded systems.

Youdong Chen (M’10) was born in Lujiang County, Anhui Province, China, in 1973. He received the B.S. degree in mechanical engineering and the Ph.D. degree in manufacturing engineering and automation from Beihang University (formerly Beijing University of Aeronautics and Astronautics), Beijing, China, in 1995 and 2003, respectively. He is currently with the School of Mechanical Engineering and Automation, Beihang University. His research interests include the areas of motion control, computer numerical control (CNC), industrial robots, and embedded systems.

Jindong Tan (M’99) received the Ph.D. degree in electrical and computer engineering from Michigan State University, East Lansing, in 2002. He is currently an Associate Professor in the Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, MI. His research interests include mobile sensor networks, wearable computing, wireless health, surgical robotics, and unmanned aerial vehicles. Dr. Tan is a member of the Association for Computing Machinery.

Tianmiao Wang (M’08) received the B.E. degree from Xian Jiaotong University, Xian, China, and the M.S. and Ph.D. degrees from the Northwestern Polytechnical University, Xian, in 1982, 1997, and 1990, respectively. He was a Postdoctoral Fellow in the State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, and the State Bionic Force Laboratory, Italy, in 1992 and 1995, respectively. Since 1998, he has been a Professor in the School of Mechanical Engineering and Automation, Beihang University (formerly Beijing University of Aeronautics and Astronautics), Beijing, China. His research interests include mircorobot technology, medical robot technology, and embedded electromechanical control technology.