Proceedings of the 2002 IEEE International Conference on Robotics & Automation Washington, DC • May 2002
Control System Design of THBIP-I Humanoid Robot Mingguo Zhao, Li Liu,Jingsong Wang, Ken Chen, Jiandong Zhao, Kai Xu Department of Precision Instrument and Mechanics, Tsinghua University, P.R. China
[email protected]
Abstract This Paper describes the progress of the control system design and implementation of THBIP-I humanoid robot over the past two years. This project involved three Laboratories responsible for lower limbs, upper limbs and general control respectively. The aim of this project is to construct a prototype anthropomorphic robot, which can work in human daily environment and can collaborate with human beings. The robot totally has 32 degree of freedoms and each joint is driven by a brushless DC electronic motor. Screw/nuts transmission mechanism is adapted in some joints of lower limbs to achieve compact and good dynamic performance. The control system of the robot has four subsystems: Remote Brain Work Station, Mobile Controller, Distributed Control Units and Sensor Processing Unit. At the Present State, the Lower limbs and upper limbs has been built and tested, and with the off line gait planning. The distributed Control Units use PID schemes to servo the pre-generated joint trajectories. Under this architecture, the robot can perform a stable walking with 30 centimeters step at 20 second per step. Advanced control schemes for dynamic walking and DSP-based Distributed Control Units are under developing and simulated in the computer software.
Introduction The primary motivation for developing humanoid robot is to perform tasks that are dangerous for human beings or as a substitution of man from some repeated works. Considering the environment that designed
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for human occupancy, such as stairs and uneven terrain, bipedal walking is one of the essential features of the humanoid robot[1,2]. There are a number of powered bipedal walking robots that have been built by various groups throughout the world. Researchers at Waseda University enjoy a long history of working on bipedal walking robots since 1969 and they developed an anthropomorphic robot—Wabian. This robot has a total of 35 degrees of freedom and relies on playing back pre-recorded joint trajectories and compliance joint control to produce more natural-looking dynamic walking[3,4]. After about ten years of research, Honda Corporation created the humanoid robot P2, P3 and Asimo, which can perform several complicated tasks such as walking on a flat ground, turning, up/down stairs, balance, and pushing objects around all in three dimensional space. The control method of Honda’s robot is using ZMP to planning the pre-recorded joint trajectories and playing them back with sensor-based compliant control[1,2]. A French group developed a 15 degrees of freedom bipedal robot—BIP2000 in 2000. Screw/nuts mechanism is adapted in motion transmission of its 10 joint and the robot first uses parallel transmitters for ankle joints motion in the lateral and sagittal planes[5,6]. Pratt et al. at MIT developed their 3D bipedal walking robot—M2 with smart Series Elastic Actuators, which is created by them. M2 copies the character of human beings and aimed at perform a natural gait in walking[7,8]. Some other bipedal or humanoid robots have been built for scientific research or commercial toy products, such as
the mechanical size and weight and for the yaw motion of ankle and hip, we use two bar linkage to provide variable transmission rate, which can provide more transmission rate at some conditions. For other joints, we use gears to transmit motor motion. Two CCD cameras are planted in the head to percept the environment. Two 6-axis force/torque sensors are placed in the foot to measure the ground reaction force and calculate ZMP position. A gyromteter and accelerometer are mounted in the robot trunk to measure the posture and body position and attitude of the robot to realize feedback control. It is nececcary for the robot to adjusted in the condition of uneven ground.
SD-2 by Professor Zheng and SDR-3X by Sony Corporation [9,10,11,12,13]. From an engineering point of view, the development of humanoid robot covers mechanical design, computer system integration, sensors design, balance control and artificial intelligence study. Inspired by the above robots, we concentrate our study on the following three parts: study of human walking inherent characters by energy analysis, development of an experimental humanoid robot hardware and study of the control scheme for natural dynamic walking and balance. A prototype robot with 32 degrees of freedom has been built and the lower limbs are shown in figure 1. The robot is170 centimeter high and weights 140 kilograms, it has 6 DOF in each leg, 7 in each arm, 2 in each hand and 2 in neck, the configuration of the robot is shown in figure 2. This configuration provides the robot with the abilities of walking on the ground, up/down stairs and hold simple object.
Fig.2 DOF Configuration of the THBIP-I Robot
Control System Hardware Architecture The control system of THBIP-I Humanoid robot is a parallel multi-computer architecture and can be divided into four parts or subsystems: Remote Brain Work Station (RBW), Mobile Controller (MC), Distributed Control Units (DCU) and Sensor Processing Unit (SPU). The RBW subsystem is responsible for path
Fig.1: The Lower Limbs of THBIP-I Humanoid Robot in Experiments Each joint of the robot is actuated by Maxon Electronic brushless DC motor. For the knee and pitch motion of hip we use screw/nuts transmitter to reduce
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system and electronic motors. In figure 3 we use red line to represent the power and green line to represent signals. The structure of Servo Control Unit is shown in figure 4. CPU1 is responsible for Communication with PC104 and generate reference signals for the 4 joint PID controllers. CPU2 is responsible for PID control of four Joints. Because the communication band wide, the high level controller generate a group of trajectories data in 50 Hz, while the low level PID control frequency is done by CPU2 is 500Hz, so a 2-port RAM is used between CPU1 and CPU2 to store the interpolated joints trajectories. A flash memory is used to store the PID schemes, resident programs running in the CPU1 and CPU2 can make the designer to change control parameters in RBW and download them to the Servo Control Unit without moving any hardware. At present the CPUs in the Servo Control Unit are ATMEL 89c55, and another DSP based Servo Control Unit and a BIOS Program are under developing for complex control schemes.
planning and some actions teleoperation, for some tasks are so complex that they cannot be operated by autonomous control schemes on the robot body. Mobile Controller is a laptop computer on the robot, which is the decision-making unit of the robot. MC collects the environment information by sensors and generates the compensate trajectories from pre-recorded joint trajectories. As shown in Figure 3, RBW and MC are connected by a wireless Ethernet and the CCD cameras are connected to MC by USB bus. Distributed Control Unit is divided into two parts: High Level Control and Low Level Control. High Level Control is composed by two PC104 embedded computer responsible for upper limbs and lower limbs respectively. Low-level control is composed by 11 PID Servo Control Units. Each Servo Control Unit is a two CPU based computer system and mounted on the limbs to control nearly three or four joints. The PC104 and Servo Control Units are connected by CAN bus and two PC104s are connected to MC with 10M Ethernet. Sensor Processing Unit is another PC104 computer, which deal with 6-axis force/torque, a gyromteter and accelerometer control and data processing. Besides these four subsystems, an energy management regulates the power supply from battery to control
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Fig.4 Diagram of Servo Control Unit
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Walking and balance control is the most important work of humanoid robot. Within our knowledge, they fall into two categories. Many use pre-recorded joint trajectories and sensor data for online compliant control approaches. Others use heuristic control scheme. At beginning, we do the same as the first method on our robot, and in the future, we will develop a control scheme for nature dynamic walking.
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Fig.3 Diagram of Control System
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Figure 5 shows the model in lateral and sagittal plan of our robot without considering the upper limbs’ motion. Supposing that the time period for a step is Tc, the time of the kth step is from kTc to (k+1)Tc, k=1,2,…. To simplify the analysis, we define that the kth walking step begins with the heel of the left foot leaving the ground at t=kTc, and ends with the heel of the left foot touching the ground at t=(k+1)Tc. Dstep denotes the length of one step. Ha denotes the Z coordinate of the highest point of the swing foot at Ta. Xhd denotes body position at the end of double supporting period. Xhs denotes body position at the end of single supporting period. θal denotes angle of ankle around roll axis. Then: t = kTc kDstep t = kTc + Td L ft (1 − cos θ a ) + La sin θ a X a (t ) = ( ) − − − D L θ L θ 1 cos sin fh a a a t = ( k + 1)Tc step (k + 1)D t = ( k + 1)Tc + Td step
La L cos θ + L sin θ a ft a a Z a (t ) = H a L cos θ + L sin θ a fh a a La
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Fig.5 Model of the THBIP-II Robot
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t = (k + 1)Tc
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Selec t w alking speed and step
kD step + X hs t = kTc X h (t ) = ( k + 1) Dstep − X hd t = kTc + Td ( k + 1) Dstep + X hs t = ( k + 1)Tc
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[Z h (t ) − Z a (t )] tan θ al Yh (t ) = − [Z h (t ) − Z a (t )] tan θ al − [Z (t ) − Z (t )] tan θ h a al
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Determ ine am ount of heel lifting Determ ine foot trajec tory
t = kTc t = kTc + Td
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Is ZMP in stability region? N
We use Vukobratovic’s ZMP Critic as flowing for balance control. n
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First, trajectories of foot and hip are designed based on studies of human gait. Then adjust hip parameters to make ZMP close to the center of stable region. Last, change the angle between the sole and the ground to make the velocities of joint smaller, so the torque decrease largely. We plan 3D smooth trajectory in sagittal plane and lateral plane separately, and the motion in the lateral plane only happens in double support phase. Figure 6 is a flowchart showing the gait generating method according to the method described above.
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Fig.6 Flowchart of gait generating
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Experiment Result
Simulation Result of static walking Gait with 30 centimeter a step at 20 seconds a step is show in figure 7, and the joint torque and energy of the simulation are shown in figure 8.
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Figure 9 shows the planning and real joint trajectories of left hip and knee. The robot can perform a balance static walking with a 30-centimeter a step and 20 seconds a step. In our experiment the vibration of the trunk is hardly affected by the walking speed, so by now our robot can only perform a static walking with a low speed. We are working on a robust control scheme and prepare to adapt a robber sole to absorb the contract force of leg down and up.
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Fig. 7 Simulation Result of Static Walking Gait with 30cm/step at 15s a step
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Fig.9 Planning and Real Joint Trajectories of left hip and knee
Future Works Based on the present experiment results, our future works involve three issues: firstly, the dynamic
Fig.8 Torque and Power during Simulation
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[6] P.Sardain, G.Bessonnet, Gait Analysis of a Human Walker wearing Robot Feet as Shoes, IEEE International Conference on Robotics and Automation, pp.2285-2292, 2001 [7] Q. Huang, et al. Balance Control of Biped Robot Combining Off-line Pattern with Real-time Modification, IEEE International Conference on Robotics and Automation, pp.3346-3352,2000 [8] A. W. Salatian, Y.F. Zheng, Gait Synthesis for a Biped Robot Climbing Slopinggg Surface Using Neural Networks, IEEE International Conference on Robotics and Automation, pp.2601-2611, 1992 [9] H.K. Lum, M. Zribi, Y.C. Soh, Planning and Control of a Biped Robot, International Journal of Engineering Science Vol: 37, pp1319-1349, 1999 [10] S. Kajita, T. Yamaura, A. Kobayashi, Dynamic Walking Control of a Biped Robot Along a Potential Energy Conserving Orbit, IEEE Transactions on Robotics and Automation, Vol.8, No. 4, pp. 431-436, 1992 [11] J. Yamaguch, N. Kinoshita, A. Takanishi, I. Kato, Development of a Dynamic Biped Walking System for Humanoi, IEEE International Conference on Robotics and Automation, pp.232-239, 1996 [12] A. Konno, N. Kato, S. Shirata, T. Furuta, Development of a Light-Weight Biped Humanoid Robot, International Conference on Intelligent Robots and Systems, pp.1565-1570, 2000 [13] Y.F.Zheng, A Neural Gait Synthesizer for Autonomous Biped Robots, IEEE International Workshop on Intelligent Robots and Systems, pp.601-607, 1990
walking with sensor feedback modification of this prototype robot; secondly, developing a active compliant joint and control schemes to deal with the double support phase; finally, humanoid inherent walking character and dynamic balance theory are our long term goal for humanoid study.
Acknowledgment This Project is supported by Tsinghua University “985” Project, we would like to thank the project committee for their financial support and all the researchers of three labs for their collaborations.
Reference [1] K.Hirai, Current and Future Perspective of Honda International Humanoid Robot, IEEE/RSJ Conference on Intelligent Robots and Systems. pp.500-508, 1997 [2] K.Hirai, Hirose M. Y HaiKawa., Takenaka T., The Development of Honda Humanoid Robot, IEEE International Conference on Robotics and Automation, pp.1321-1326, 1998 [3] B.Espian, P.Sardain, The Anthropomorphic Biped Robot BIP2000, IEEE International Conference on Robotics and Automation, pp.3997-4002,2001 [4] J Hu., J.Pratt, G.Pratt, Stable Adaptive Control of a Bipedal Walking Robot with CMAC Neural Networks, IEEE International Conference on Robotics and Automation, pp.1050-1056 [5] J.Pratt, Exploiting Inherent Robustness and Natural Dynamics in the Control of Bipedal Walking Robots, PhD thesis of MIT, 2000
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