022 Hexapods for robot soccer

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Information about 022 Hexapods for robot soccer
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Published on December 31, 2007

Author: Flemel

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Research on Robot Soccer and what PSU can do:  Research on Robot Soccer and what PSU can do The perceptions :  The perceptions Three perceptions: see, hear and sense_body. All related to one system of perception. Representation of perceptions: (see 1 (ball …) …) Visual Perception:  Visual Perception see. List of objects recognized: type, direction, distance, speed, number. Lines, gates, boundaries, ball. sense_body:  sense_body Force detection Energy available. Principal actions: dash, kick, turn say. Actions Slide5:  Role level : Determines the roles of each robot. (defender, attacker and goal keeper) Action level : Selects actions of each robot. (shooting, blocking, dribbling, etc) Behavior level : Move and obstacle avoidance Execution level : Motor control Role level Variants of Control structure Classification of Robot Soccer Systems:  Vision-based system Remote brainless system Brain-on-board system Robot-based system Selection guidelines Developer’s interests Computational capabilities of host computer and vision system Capabilities of the robots Cost The system can be classified using the location of intelligence Classification of Robot Soccer Systems Remote-Brainless System:  Centralized system Simple and inexpensive Easy to develop the robot No local sensors. Fast computing time and sampling time Easy to debug and upgrade the program Remote-Brainless System High cost vision system and host computer A type of vision-based system Intelligent part is implemented in the host computer. Remote-Brainless System:  Robots The robots consist of driving mechanism, communication part, and computational part for velocity and for processing the data received from a host computer Host computer All the calculations for vision data processing, strategies, position control of robots and so on, are done in the host computer which controls robots like radio -controlled car Remote-Brainless System Brain-on-board system :  Brain-on-board system Intermediate level between the centralized and the distributed systems / between the remote-brainless and the robot based systems. Robots can use local sensors to move to the goal and to avoid the opponent. Can decompose the system into high level (host computer) and low level (robot systems). Easy to make the system in modular form A type of vision-based system Intelligence is partially implemented in the host computer and robots. Brain-on-board system :  Robots The robots have functions such as velocity control, position control, obstacle avoidance, etc. Host computer The host computer processes vision data and calculates next behaviors of robots according to strategies and sends commands to the robots using RF modem. Brain-on-board system Robot-based system:  Robot-based system Suitable when the large number of agents exist Complex and expensive Need communication among robots Distributed system Intelligent part is implemented in the robots. Robot-based system:  Robots The robots decide their own behavior autonomously using the received vision data, own sensor data and strategies. Host computer The host computer processes only vision data can be considered as a kind of sensor. Robot-based system Main PC:  Main PC Serial Port Select the serial communication port Home Goal Select the home side on the screen Find Objects Check the box of which you like to find on the field Initial Position: tell the vision system the initial position of each object E.g.) for the ball i) turn on the radio button of ‘Ball’ ii) place the mouse on the ball and press the left button Repeat above procedure for another object EXAMPLE Main PC:  Main PC Select Situation The situation in which the game is about to start Command Click ‘Ready’: the vision system starts finding the objects on the field Click ‘Start’ : the vision system starts sending commands to the robots Click ‘Stop’ : the vision system stops finding objects and sending commands EXAMPLE Communication (Infra-red):  Communication (Infra-red) Infra-red Communication Four transmitters are used to cover the whole field EXAMPLE Communication:  Communication Both teams share the same transmitter via a mediator Communication Packet Three 0xFFs: the start of a packet 0x0F (0xF0): Team A (Team B) VLi , VRi: left and right wheel velocity of robot i 0xAA: end of velocity data of each robot EXAMPLE Tough, practical problems to be solved:  Tough, practical problems to be solved Real-Time image processing Sensor fusion (sonar, touch, vision, light, other). Motors, batteries. Sophisticated control strategies Radio communication Agent communication Problems :  Problems Players do not know absolute locations. Points of reference are: boundaries, lines and gates. Conflicts of players Limited visibility Limited communication Software:  Software Real-Time Problem, rule-based, agent behavior. Dynamic planning and execution of plans in real-time. Cooperation and competition. No precise information Non-deterministic behavior: results of actions are uncertain. Software potentials (cont.):  Software potentials (cont.) Voice comunication of players Various players have different rules and behaviors, different strategies and implementations - rule-based, neural nets, fuzzy logic, etc. multi-agents: competition versus collaboration. on-line versus off-line, individual versus group behaviors. FIRA and the ECE 478/ECE 479 class at PSU:  FIRA and the ECE 478/ECE 479 class at PSU Class project and in future Capstone Project (if a company will sponsor) High-School project Portland Cyber Theatre Experience in Visual C++, Basic, Lisp and Prolog programming. A lot of fun. Travel to Japan or Korea? Does PSU team has a chance?:  Does PSU team has a chance? 1. Professor Kim from KAIST in Korea invited us to create a new league of walking robots 2. We have experience with walking robots 3. We will try to propose new competition ideas and have a leverage of knowing them earlier. Besides, our students are smart…..? Let us look to our robots…... What we propose:  What we propose Robot soccer system Intelligent control system Multi-agent system Composition of robot soccer system Mobile robots Host computer Vision system Communication module Sports commentator Walking robots Team One:  Team One Complex robots 8 to 12 servos Our walking quadrupeds and hexapods:  Our walking quadrupeds and hexapods Collaborations: ATR, Japan Technical University of Warsaw, Poland Technical University of Gliwice, Poland KAIST, Korea Multi-national team Quadruped :  Quadruped Basic Radio-Controlled Spider Hexapod with Gripper:  Basic Radio-Controlled Spider Hexapod with Gripper Spider with a camera:  Spider with a camera New soccer-specialized hexapod:  New soccer-specialized hexapod Hexapod’s Soccer Kicker:  Hexapod’s Soccer Kicker Team Two:  Team Two Simple robots - hexapods 2 servos SoccerBot:  SoccerBot Final design of a quadruped walker:  Final design of a quadruped walker Block Diagram of the Simple Robot System:  Block Diagram of the Simple Robot System Logic Power PWM Right PWM Left Motor Driver Motor Driver Motor Motor Voltage Regulator Motor Power Micro-Controller Battery Communication Signal Communication Module Motor Part Sport Commentators:  Sport Commentators Bug Virginia Woolf:  Virginia Woolf Jonas:  Jonas Marvin the Crazy Robot:  Marvin the Crazy Robot Class Projects - Winter/Spring 2002:  Class Projects - Winter/Spring 2002 1. Robot position, orientation and conflict detection using top-mounted camera 2. Ball recognition and vision interface to the server 3. Server and user interface 4. Egoistic soccer-playing strategy 5. Collaborative soccer-playing strategy 6. Recovery from body conflicts such as leg entanglements of robots Class Projects - Winter/Spring 2002:  Class Projects - Winter/Spring 2002 7. Design of robo-head sport commentator: speech and natural language generation. 8. Mechanical improvements to robots 9. Design of a special soccer player hexapod. Slide42:  Image Processing: find position, orientation and conflicts of a walker Slide43:  Filtering, histogramming, Hough transform, equations Localization, orientation, conflicts (leg entanglements) Robo Soccer - Why is it so cool?:  Robo Soccer - Why is it so cool? Is Robot Soccer useful? Is the result of Robot Soccer useful? Is Robot Soccer the worlds largest playground? Is there money to be made with robots to play sports? Why are Robot Sports so cool? :  Why are Robot Sports so cool? Captures the essence of soccer. (That’s why there can be a lot of people cheering on the teams) ”Hacker-party” more than a dull academic conference….that is, it is a lot of activity. Interesting problem in co-ordinating 11 processes to achieve a common goal. The width of the field, from Robotic-nerds to Sociologists. Why are Robot Sports so cool? :  In the simulator league, you are forced to learn many concepts: for example network communication, multi-threading, agents, hardware, etc. Testbed for AI-algorithms, sociological theories. Fairly simple environment. A limited set of rules (also predefined), but always close to real world problems. Why are Robot Sports so cool? What are the problems with Robot Competitions ? :  What are the problems with Robot Competitions ? Too much work before reaching an interesting research level Too much focus on low level implementation (still) Still focus on competing instead of comparing of strategies. Research:  Research We do research in several areas: Machine learning (constructive induction) Decision theory Social agents walker’s gaits evolution +more In all of the above we plan to use robot sports as a testbed, or applied area. Conclusion:  Conclusion Robot sports areTHE new standard problem within AI. 1500 researchers world-wide. Focuses on interdisciplinary co-operative work between the researchers as well as co-operation between the agents. New experience for PSU Current class:  Current class 4 ME students 3 CS students 3 EE students Using existing robots CS and EE students develop software ME students develop 2 new robot prototypes and kits with good documentation CS and EE students build new robots from kits ME students adopt software to new robots and learn programming 6 robots of two types build and tested in July Current class:  Current class 4 ME students 3 CS students 3 EE students Using existing robots CS and EE students develop software ME students develop 2 new robot prototypes and kits with good documentation CS and EE students build new robots from kits ME students adopt software to new robots and learn programming 6 robots of two types build and tested in July Technical Publications :  Technical Publications Hiroaki Kitano, Masahiro Fujita, Stephane Zrehen , and Koji Kageyama, "Sony Legged Robot for RoboCup Challenge", In Proceedings of the IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, IEEE, 1998, pp.2605-2612 Manuela Veloso, William Uther, Masahiro Fujita, Minoru Asada, and Hiroaki Kitano, "Playing Soccer with Legged Robot", In Proceedings of the INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, 1998, pp.437-442 Let us go deeper How to find more about RoboCup?:  How to find more about RoboCup? Web Pages: http://medialab.di.unipi.it/Project/Robocup http://www.robocup.org http://www.dsv.su.se/~robocup

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