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UCSD CSE 190 - Rat’s Life Competition Entry

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Ra t’s Life Competition Entry Thavidu Ranatunga ANU-UCSD Exchange Student 2009 [email protected] Abstract The proposed project is an entry into the Rat’s Life robotics competition, which can be carried out in both simulated and real forms (using LEGO setups). The competition pits pairs of robots in a maze with the objective of out lasting the other robot. The task is measured by an energy level which may be recharged from sources within in and unknown maze configuration. Robots are equipped with 8 distance sensors, a camera, an accelerometer, 10 LED lights and 2 wheels. The project aims to create a competitive entry, and will most essentially require the use of image processing, motor control, autonomous management of resources, landmark based navigation and mapping. 1 Qualifications I have competed in several AI-based competitions that required a focus on mapping and autonomous management in the past, including the Imagine Cup and Robochamps. I have also created similar programs for tasks at the Australian Informatics Olympiad and for assignments in COMP2300 (at my home university of ANU). I will also be concurrently enrolled in ECE173 at UCSD during the same semester. 2 Description The objective of the project is to create an competitive entry into the Rats Life competition running at http://www.ratslife.org The competition is defined in both simulated and real platforms however we will be referring to the simulated platform hence forth. The competition runs matches of two robots in a random maze configuration containing power sources (‘Feeders’), walls, landmarks and open spaces. The robots have a simulated ‘energy level’ which depletes over time and the robots must recharge at power sources in order to stay active. ‘Feeders’ require time to recharge once they have distributed their allocated power. The objective of the competition is to outlast the opposing robot. Robots have 4 types of sensors; these include 8 distance sensors, an accelerometer, 2 wheel encoders and a camera. Outputs are 2 wheels and 10 LED lights on the robot.In order to be able to be competitive, the robot will need to be able to - Create and maintain a dynamic map of its surrounding environment, including mapping any visible landmarks - Identify ‘feeder’ power sources and recognize whether they are an active or inactive state - Use the gathered information to move around the maze efficiently and without crashing into walls - Manage its power supply so as to stay active as long as possible Thus a competitive, intelligent entry will require use of techniques in image processing, motor control, autonomous management of resources, landmark based navigation and mapping. Existing strategies for entries to Rat’s Life vary from random/luck-based to more systematic approaches, and both have their benefits depending on which maze configuration arises. Thus a balance needs to be sought between the two, and a good strategy is possibly one that can switch or adapt based on the limited observability of the maze. 3 Goals & Milestones - (Ongoing) Compare efficiency against other robots online and keep track of progress - (Weeks 1-4) Robot is able to create a map of its surrounding environment and continuously update it. Robot is also able to move and keep track of its location within this map. (Motor Control & Distance Sensors) o (By week 6) Robot is able to identify landmarks via camera and include them in the map (Image processing & Mapping) - (Weeks 3-5) Able to identify a ‘Feeder’ source via the camera (Image processing) o (By week 6) Robot is able determine a ‘Feeder’s status; active / recharging (Image processing) - (Weeks 6-9) Focus on algorithms and strategy for efficiently managing energy and navigating the maze - (Week 10) Finalize entry; use the most efficient entry/algorithm created thus far. 4 Questions - What are the biggest obstacles for efficiently traversing the maze? - What strategies are better in which maze configurations? - What was on average the best strategy for managing energy? - Does attempting to learn/adapt and switch to a more extremist strategy autonomously produce negative results? 5 Software To control the robot I will be using the Webots software affiliated with the competition and the framework provided by the organizers of Rat’s Life. The framework is based in Java 1.6.0_06. This provides a simulated environment to test the robot and conduct matches. The robot controller software is cross platform and can be transferred if desired onto a real LEGO-based environment with e-puck robot hardware.6 Data There is a database of more than 50gb of data containing 2500 movies of simulated matches from the first Rat’s Life competition which ran for six months from January to July 2008; this data may be used for comparison purposes and is available on the Rat’s Life competition website1. There is also an unofficial contest for the out-of-season period (of the official contest) at http://www.theprovinggrounds.net/ratslife/ which I will be using both for data and for testing. References [1] Bertoli, P., Cimatti, A., Roveri, M., Traverso, M. (2006) Strong planning under partial observability. Artificial Intelligence, 170 [2] Michel, O., Rohrer, F. (2008) The Rat’s Life Benchmark: Competing Cognitive Robots. European Robotics Symposium [3] Austin, E., Parr, R. (2003) DP-SLAM: Fast, robust simultaneous localization and mapping without predetermined landmarks. Proceedings of International Joint Conference on Artificial Intelligence [4] Haehnel, D., Fox, D., Burgard, W., Thrun, S. (2003) A highly efficient FastSLAM algorithm for generating cyclic maps of large-scale environments from raw laser range measurements. Procedings of the Conference on Intelligent Robots and Systems. 1


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UCSD CSE 190 - Rat’s Life Competition Entry

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