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Carnegie Mellon Robotics Institute

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Abstract

Several researchers in robotics and artificial intelligence have found that the commonly used method of planning in a state (configuration) space is intractable in certain domains. This may be because the C-space has very high dimensionality, the "C-space obstacles" are too difficult to compute, or because a mapping between desired states and actions is not straightforward. Instead of using an inverse model that relates a desired state to an action to be executed by a robot, we have used a methodology that selects between the feasible actions that a robot might execute, in effect, circumventing many of the problems faced by configuration space planners. In this paper we discuss the implications of such a method and present two examples of working systems that employ this methodology. One system drives an autonomous cross-country vehicle while the other controls a robotic excavator performing a trenching operation.

Notes

Text Reference

Sanjiv Singh and Alonzo Kelly, "Robot Planning in the Space of Feasible Actions: Two Examples," Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '96), April, 1996, pp. 3309 - 3316.

BibTeX Reference

@inproceedings{Singh_1996_798,
   author = "Sanjiv Singh and Alonzo Kelly",
   title = "Robot Planning in the Space of Feasible Actions: Two Examples",
   booktitle = "Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '96)",
   pages = "3309 - 3316",
   month = "April",
   year = "1996",
   volume = "4",
}

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