A Remote Laboratory for Teaching Mobile Robotics - CiteSeerX

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A Remote Laboratory for Teaching Mobile Robotics F. Rodriguez, A. Khamis, R. Barber, and M. Salichs

Abstract-- This paper presents the current contribution of Carlos III University (UC3M) in the Innovative Educational Concepts for Autonomous and Teleoperated Systems (IECAT) project which aims at create an innovative educational tool to allow students to perform remote laboratory experiments on autonomous and teleoperated mechatronic systems [1]. UC3M will provide remote experiments on indoor mobile robotics, addressing different approaches to solve the main problems of mobile robots, such as sensing, motion control, localization, world modeling, planning, etc. These experiments will be used on several mobile robotics and autonomous systems courses, at the undergraduate and graduate levels, at several universities involved in the IECAT project.

reaches users; these factors play an important role in user adoption of remote laboratories. The main problems of remote control robotics have been addressed in [3]. Barney and Ken have presented a communication framework to enable control and collaboration between multiple users of a distributed robotics system over the Internet [4]. The World Wide Web has already been used as a tool to provide an open access to mobile robots [5-7]. Some Web-based interfaces for remote control of mobile robots operating in public places are presented in [8], where remote visitors can access a museum exhibition. II. SYSTEM DESCRIPTION

Index Terms—Internet, Object-oriented Methods, Robotics, Teaching Method. I.

INTRODUCTION

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OWADAYS Internet is considered a global integrated communication infrastructure that enables an easy implementation of distributed systems. For this reason, a great attention is being paid now to use the World Wide Web as a tool for building remote laboratories for tele-education on mechatronics. Tele-education can be defined as a networkbased educational environment where the telecommunication technologies are used to map the traditional teaching and learning activities [2]. The most important benefit of such systems is the expected growth of the participation level in the education process. This growth is due to increasing system flexibility and expanding the accessibility and availability of updated materials. Robotics education provides an ideal field for teleeducation systems because its flexibility. Unlike traditional fields, robotics is still an emerging area. Relatively few programs exist at the graduate level, and even fewer exist at the undergraduate level. The courses in existence are still new and are open to rapid change and new approaches. The remote laboratories provide a live performance laboratory accessible via Internet, which can be used to cover the experimental issues in any tele-education system. Clearly as bandwidth increases and higher speed network access

Manuscript received November 6, 2001. This work is being funded by the Directorate General for Education and Culture of the European Commission under the EC/USA Program for cooperation in Higher Education and Vocational Education and Training.

A. Remote Laboratory Overview The concept of remote laboratories has been proposed in the expert meeting on virtual laboratories [9]. It has been defined as an electronic workspace for distance collaboration and experimentation in research or other creative activity, to generate and deliver results using distributed information and communication technologies. To implement a remote laboratory, a common Internet-based teleoperation model is used as shown in Fig.1.

Fig.1 Internet-based Teleoperation Model This model is based on the simple protocol commonly used in distributed computation "The Request/Response Protocol". The client interacts with the system using any Web browser to make the request. Client' requests are translated to HTTP

IFAC TA 2001 requests, which satisfied by the Web server. These request are converted to high-level control requests that received by the robot controller to transmit them as low level control requests to execute the required task. Sensory feedback is required to give the user information about the remote robot's environment and the consequences of his/her commands. By using the concepts derived from this simple model, a remote laboratory can be developed to provide live performance experimentation. Students will be able to access remote experiments for learning the systematic knowledge of mobile robotics like: 1) Range Sensors: Information of the environment is obtained, using sonar and laser sensors, from different robot positions. The experiment shows to the students the problems and limitations of this kind of sensors. 2) Perception of environment features with range sensors: The information from range sensors is processed by different algorithms able to extract environment features such as corners, walls, doors, etc.… 3) Perception of environment features with computer vision: Visual information of the environment is processed to extract representative visual environment elements. 4) Basic motion control skills: Different motion control strategies are used to obtain robot behaviors such go to goal, path following, wall following, corridor following, approaching, etc. The students also lean the importance of properly tuning the parameters of the control algorithms. 5) Fusion of motion control skills: Different strategies are used to fuse simple motion control skills in order to obtain complex behaviors such us path following avoiding obstacles. 6) Environment modeling: The data obtained from the sonar and laser sensors is used to model the environment with occupancy grids. The student can change different parameters, such as the grid size, and study the effects of moving objects. 7) Geometric localization: The position and orientation of the robot is firsts calculated using odometry or the relative position of the robot with respect to external landmarks, studying the inaccuracies of both methods. Then the different sources of information are fused using a Kalman filter. 8) Simultaneous localization and mapping: The localization of the robot and environment features is simultaneously calculated using a Kalman filter. 9) Topologic navigation: The robot navigate using only its relative position in relation to elements of the environment, using a predefined topological map.

2 B. Mobile Robot Description The used robot is indoor mobile robot B21 from Real World Interface [10] with mobility software. The B21 hardware consists of two main sections, the base and the enclosure. The base contains the batteries and the motors (4 high torque, 48 VDC servo motors with 4-wheel synchronous drive) which translate (90 cm/s with resolution 1 mm) and rotate (167 º/s with resolution 0.35º) the robot, as well as a dedicated microprocessors which handle very low level functions such as dead reckoning. The enclosure contains two main computers, a power distribution system and on the top of the enclosure it is mounted a camera. Moreover the B21 has the following sensors: - Laser Sensor, which covers 180 degree scan range; - Sonar Sensors, B21 contains 24 sonar sensors. Each sensor has a beam width of 15 degrees, and the range to an object is determined by the time of flight of an acoustic signal generated by the transducer and reflected from the object. The robot can use the sensors to detect the range information from 15 cm to 1067 cm around the robot. - Tactile Sensors (56 – 32 base, 24 enclosure), which are used to detect contact with objects. These sensors are organized in two ranges to provide 360 degrees coverage. Each tactile sensor is a switch on/off state. - Infrared sensors (IR), B21 contains 56 IR sensors (32 base, 24 enclosure) these sensors can detect very near objects. - CCD Camera for image processing. III.

REMOTE LABORATORY ARCHITECTURE

To obtain maximum level of portability, an important design decision was that all interactions with the remote laboratory under developing could be accomplished with only a Web-browser as an interface, no additional software or plug-ins should be needed for the use of the laboratory. Fig.2 shows the remote laboratory architecture, which is a multilayered architecture to facilitate quick start-up and an unprecedented level of code re-use and transportability.

Fig. 2 System Architecture

IFAC TA 2001 With Java, we can provide a cross-platform user interface for configuration, testing and visualization of our robot software system in action. The proposed architecture consists of the following layers: A. Student Layer Clients can access to the experiment using any Webbrowser (Netscape or Internet Explorer). Users request are received by Java applets and events sent to the corresponding Java Servlet in the Web server. B. Middleware Layer In this layer, there is a PC internally linked to an Ethernet lan and externally to the university's Intranet. It runs Apache Web server, which contains the HTML files and fours Java servlets (Drive to respond to motion commands, odometry to provide the robot's position, sonar to provide sensorial information of the sonar sensor and the laser servlet to provide the laser range finder readings). Our selection to Apache Web server is based on a comparison between the commonly used Web servers, Apache, MS Internet Information Server and Netscape Enterprise Server [11-12]. C. Robot Layer The robot layer has a two level architecture called AD (Deliberative and Automatic levels) based on skills[13]. A skill represents the robot ability to perform a particular task. In the deliberative level there are skills capable of carrying out high level tasks, while at the automatic level there are skills in charge of interacting with the environment. The path planner, the environment modeler and the task supervisor are some of the skills included in the deliberative level. The sensorimotor and the sensorial skills are found in the automatic level. The first ones are in charge of the robot motion. The second ones proportionate the events needed to produce the sequencer transitions which manage the task the performed by the robot. In the AD architecture, skills are client-server modules. Each skill is implemented as a distributed object. Each skill is activated by the deliberative level sequencers. During the period of time in which the skills remain active, it can connect to data objects of other skills or to sensorial servers (Odometry, sonar, laser and camera) . As a result the skills can either generate motor actions over the robot actuators (through a drive server), when considering sensorimotor skill, or event, when sensorial skills are considered. The skill outputs –actions and events- are stored in its data objects. The communication between the servlets and the remote robot skill servers is done via the Object Request Broker (ORB) of the Common Object Request Broker Architecture (CORBA) where the Java servlet acts as a client to the robot skill. The ORB provides the communication via the unified interface language Interface Definition Language (IDL) and based on the Internet Inter-ORB protocol (IIOP) [14].

3 The decision of using CORBA as the distributed object architecture of the remote laboratory is based on a qualitative and quantitative comparison between the two most commonly used architecture, CORBA and RMI [15]. This study concluded that CORBA is suitable for large scale or partially Web-enabled applications where legacy support is needed and good performance under heavy client load are expected moreover CORBA servers can be located at any Internet site. RMI, on the other hand, is suitable for small scale fully Webenabled applications where legacy support can be managed with custom build or prebuild bridges, where ease of learning and ease of use is more critical than performance. IV. REMOTE LABORATORY IMPLEMENTATION An online laboratory in a field as mobile robotics must have a live performance characteristic, not just virtual reality or simulation programs. The multilayered architecture, described in the previous section, is being currently implemented to reach this goal. The student will communicate and teleoperate the experiment using a Java applet in a Web browser as shown in Fig.3. The task is then executed by a local control system and the results displayed on the operator’s browser. This client-level interface includes many operations that can be made on the robot such as position control, obtaining sensors data, drawing world maps and evaluate the errors. The following subsections describe the objectives and the steps of an experiment.

Fig. 3 Online Experiment Interface A. Experiment Objectives This experiment has two objectives. The first one is familiarize the user with the mobile robot motion control and positioning. The second objective is the environment perception using multisensor data (sonar and laser). B. Experiment Steps •

Environment measuring with the ultrasonic sensors using both point and segment views as shown in Fig.4 and Fig.5.

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Interpretation of the data where the student must draw a possible world map. Repeat the first and the second steps, for different robot positions. Robot position can be changed by sending position control commands. Repeat the first and the second steps, using point and segment data views from laser range finder as shown in Fig.6 and Fig.7. Compare the previous results with the real map of the environment. Evaluation of the errors.

C. Result Analysis After finishing the experiment steps, the user can easily predict the obstacle zones by comparing the real environment with the superposed sensorial data as shown in Fig. 8. The out of range unpredicted values in both sonar and laser readings are due to the existence of some transparent objects in the lab as windows and fireboxes or due to the reflections from sharp edges.

Fig.6 Laser Point View

Fig. 7 Laser Segment View

Fig. 4 Sonar Point View

Fig. 8 Real Environment and Sensorial Data V. CONCLUSION

Fig. 5 Sonar Segment View

Web-based robotics introduce innovative educational tools in the area of mechatronics, where World Wide Web can be used as cheap, reliable and interactive infrastructure. This article has summarized the current and future contributions of UC3M in the IECAT project. It described a remote laboratory architecture for teaching mobile robotics

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IECAT Project Homepage, 2001. http://www.ars-sun4.ars.fhweingarten.de/iecat/ F. Rodriguez, A. Khamis, and M. Salichs, "Teaching Mobile Robotics to anyone, anywhere at anytime," 1st Workshop on Robotics Education and Training, RET 2001, Weingarten, Germany, pp.75-80, Jul 2001. C., Sayers. Remote Control Robotics. 1st Edition, Springer Verlag, 1999. D. Barney, and T. Ken, "Distributed Robotics over the Internet," IEEE Robotics and Automation Magazine, vol.7, no.2, pp.22 -27, 2000. P. Saucy, and F. Mondada, "Khepontheweb: Open Access to a Mobile Robot on the Internet,", IEEE Robotics and Automation Magazine, vol.7, no.1, pp.41-47, 2000. G. Guimaraes, T. Maffeis, L. Pereira, G. Russo, M. Bergerman, E. Cardozo, and F. Magalhaes, "REAL: A Virtual Laboratory for Mobile Robot Experiments," 1 st IFAC Conference on Telematics Applications in Automation and Robotics, TA 2001, pp.209-214, Weingarten, Germany, 2001. O. Rosch, K. Schilling, and H. Roth, "Haptic Interfaces for Remote Control of Mobile Robots," 1st IFAC Conference on Telematics Applications in Automation and Robotics, TA 2001, pp.143-147, Weingarten, Germany, 2001. D. Schulz, W. Burgaed, D. Fox, S. Thurn and A. Cremers, "Web Interfaces for Mobile Robots in Public Places," IEEE Robotics and Automation Magazine, vol.7, no.1, pp.48-56, 2000. IITAP, Report of the Expert Meeting on Virtual Laboratory, International Institute of Theoretical and Applied Physics, Ames, Iowa, 10 Dec. 1999. Real World Interface, http://www.irobot.com/rwi/ A. Abualsamid, "Evaluacion de las Herramientas de Desarrollo," Global Communication, No. 31, pp. 52-55, Dec. 1999. G. Yerxa, "Las Mejores Apuestas para el Desarrollo Web," Global Communications, No. 31, pp. 44-51, Dec. 1999. Barber, R., Salichs, M.A. (2001) “A new human based architecture for intelligent autonomous robots”. The Fourth IFAC Symposium on Intelligent Autonomous Vehicles, p85-90. Sapporo, Japan. September 2001. Object Management Group, http://www.omg.org/ M. Juric, I. Rozman, and M. Hericko," Performance Comparison of CORBA and RMI," Information and Software Technology, No. 42, pp. 915-933, 2000.

F. Rodriguez is Associate Professor of system Engineering and Automation at the University Carlos III of Madrid, Spain. He received the Ph.D. degree in Artificial Intelligence and Robotics from the Polytechnic University of Madrid, Spain, in 1993. His current research interests concern a robotics and teleeducation systems. A. Khamis received the B.Sc. degree in Electrical Engineering from Alexandria University, Egypt, in 1993, the M.Sc. degree in Electrical Engineering from Suez Canal University, Egypt, in 1998, and is currently pursuing the Ph.D. degree in Industrial Technology, at University Carlos III of Madrid, Spain. In the academic years 1995-99, he worked for the Engin eering Sciences Department at Faculty of Petroleum and Mining Engineering, Suez Canal University as a demonstrator and assistant lecturer. In 1998, he developed an expert system to deal with the electrical safety problems in the large industrial petrochemical plants. His present research is primarily focused on tele-education systems and mobile robotics. R. Barber is a research assistant of the System Engineering and Automation Unit, at the University Carlos III of Madrid, Spain. He received the B.Sc. deg ree in Industrial Engineering from Polytechnic University of Madrid, in 1994, and the Ph. D. degree in Industrial Technologies from the University Carlos III. In 2000 has developed a new control architecture for mobile robots based on topological navigation. His current research area is automatic generation of topological maps. This author is member of the International Federation of Automatic Control (IFAC). M. Salichs received the Electrical Engineering and Ph.D. degress from Politechnical University of Madrid in 1978 and 1982, respectively. He is currently a Full Professor of Systems Engineering and Automation at the University Carlos III of Madrid. He is Chairman of the Technical Committee on Intelligent Autonomous Vehicles of the International Federation on Automatic

Control (IFAC). He has published more than 80 papers on robotics and automation. His primary research interests are mobile robotics, intelligent autonomous systems and service and personal robots.