Robust Belief-Based Execution of Manipulation Programs
作者： Tomas Lozano-Perez , Leslie Pack Kaelbling , Kaijen Hsiao
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摘要: We describe a simple approach for executing manipulation programs in the presence of significant, but bounded, uncertainty. The key idea is to maintain belief-state (a probability distribution over world states) and execute fixed trajectories relative most-likely state world. These world-relative trajectories, as well transition observation models needed belief update, are all constructed off-line, so does not require any on-line motion planning.
参考文章(25)
Anna Petrovskaya, Andrew Y. Ng, Probabilistic mobile manipulation in dynamic environments, with application to opening doors international joint conference on artificial intelligence. pp. 2178- 2184 ,(2007)
Sven Koenig, Reid Simmons, Probabilistic robot navigation in partially observable environments international joint conference on artificial intelligence. pp. 1080- 1087 ,(1995)
Jean-Claude Latombe, Robot Motion Planning ,(1990)
Sam Prentice, Nicholas Roy, The Belief Roadmap: Efficient Planning in Linear POMDPs by Factoring the Covariance ISRR. pp. 293- 305 ,(2010) , 10.1007/978-3-642-14743-2_25
R. Alterovitz, T. Simeon, K. Goldberg, The stochastic motion roadmap: A sampling framework for planning with Markov motion uncertainty robotics science and systems. ,vol. 03, ,(2007) , 10.15607/RSS.2007.III.030
S.M. Lavalle, S.A. Hutchinson, An objective-based stochastic framework for manipulation planning intelligent robots and systems. ,vol. 3, pp. 1772- 1779 ,(1994) , 10.1109/IROS.1994.407618
Randy C. Brost, Alan D. Christiansen, Probabilistic analysis of manipulation tasks: a conceptual framework The International Journal of Robotics Research. ,vol. 15, pp. 1- 23 ,(1996) , 10.1177/027836499601500101
Tomás Lozano-Pérez, Matthew T. Mason, Russell H. Taylor, Automatic Synthesis of Fine-Motion Strategies for Robots The International Journal of Robotics Research. ,vol. 3, pp. 3- 24 ,(1984) , 10.1177/027836498400300101
J.P. Gonzalez, A. Stentz, Planning with uncertainty in position an optimal and efficient planner intelligent robots and systems. pp. 2435- 2442 ,(2005) , 10.1109/IROS.2005.1545048
K. Gadeyne, T. Lefebvre, H. Bruyninckx, Bayesian Hybrid Model-State Estimation Applied to Simultaneous Contact Formation Recognition and Geometrical Parameter Estimation The International Journal of Robotics Research. ,vol. 24, pp. 615- 630 ,(2005) , 10.1177/0278364905056196