Advances in Plan-Based Control of Robotic Agents: by Rachid Alami, Silvia Silva da Costa Bothelho (auth.),

By Rachid Alami, Silvia Silva da Costa Bothelho (auth.), Michael Beetz, Joachim Hertzberg, Malik Ghallab, Martha E. Pollack (eds.)

In fresh years, self sustaining robots, together with Xavier, Martha [1], Rhino [2,3], Minerva,and distant Agent, have proven striking functionality in long term demonstrations. In NASA’s Deep house application, for instance, an - tonomous spacecraft controller, known as the distant Agent [5], has autonomously played a scienti?c test in area. At Carnegie Mellon collage, Xavier [6], one other self sustaining cellular robotic, navigated via an o?ce - vironment for greater than a 12 months, permitting humans to factor navigation instructions and visual display unit their execution through the net. In 1998, Minerva [7] acted for thirteen days as a museum tourguide within the Smithsonian Museum, and led a number of thousand humans via an exhibition. those self reliant robots have in universal that they depend on plan-based c- trol for you to in achieving higher problem-solving competence. within the plan-based method, robots generate keep watch over activities via holding and executing a plan that's e?ective and has a excessive anticipated application with admire to the robots’ c- lease targets and ideology. Plans are robotic keep watch over courses robotic cannot in simple terms execute but additionally cause approximately and control [4]. therefore, a plan-based c- troller is ready to deal with and adapt the robot’s meant plan of action — the plan — whereas executing it and will thereby greater in attaining complicated and altering tasks.

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Journal of Autonomous Agents and Multi-Agent Systems, 4:25–55, March/June 2001. BHKS99. T. Bandlow, R. Hanek, M. Klupsch, and T. Schmitt. Agilo RoboCuppers: RoboCup Team Description. In Third International Workshop on RoboCup (Robot World Cup Soccer Games and Conferences), 1999. BRST00. C. Boutilier, R. Reiter, M. Soutchanski, and S. Thrun. Decision-theoretic, high-level robot programming in the situation calculus. In Proceedings of the AAAI National Conference on Artificial Intelligence, Austin, TX, 2000.

In Third International Workshop on RoboCup (Robot World Cup Soccer Games and Conferences), 1999. BRST00. C. Boutilier, R. Reiter, M. Soutchanski, and S. Thrun. Decision-theoretic, high-level robot programming in the situation calculus. In Proceedings of the AAAI National Conference on Artificial Intelligence, Austin, TX, 2000. CB97. Thomas R. Collins and Tucker R. Balch. Teaming up: Georgia tech’s multi-robot competition teams. In Proceedings of the 14th National Conference on Artificial Intelligence and 9th Innovative Applications of Artificial Intelligence Conference (AAAI’97/IAAI’97), pages 785–786, Menlo Park, July 27–31 1997.

Merke, D. Meier, A. Hoffmann, A. Sinner, O. Thate, Ch. Ehrmann. Karlsruhe Brainstormers 2000 - A Reinforcement Learning approach to robotic soccer. 2000. SAB+ 00. P. Stone, M. Asada, T. Balch, R. D’Andrea, M. Fujita, B. Hengst, G. Kraetzschmar, P. Lima, N. Lau, H. Lund, D. Polani, P. Scerri, S. Tadokoro, T. Weigel, and G. Wyeth. Robocup-2000: The fourth robotic soccer world championships. AI Magazine, pages 495–508, 2000. SBHB02. T. Schmitt, M. Beetz, R. Hanek, and S. Buck. Watch their moves: Applying probabilistic multiple object tracking to autonomous robot soccer.

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