Empirical verification of fine-motoion planning theories
Conference
·
OSTI ID:76365
- Sandia National Labs., Albuquerque, NM (United States)
- Tulane Univ., New Orleans, LA (United States). Dept. of Computer Science
Successful robot systems must employ actions that are robust in the face of task uncertainty. Toward this end, Lozano-Perez, Mason, and Taylor developed a model of manipulation tasks that explicitly considers task uncertainty. In this paper we study the utility of this model applied to real-world tasks. We report the results of two experiments that highlight the strengths and weaknesses of the LMT approach. The first experiment showed that the LMT formalism can successfully plan solutions for a complex real-world task. The second experiment showed a task that the formalism is fundamentally incapable of solving.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 76365
- Report Number(s):
- SAND--95-1192C; CONF-9506196--1; ON: DE95013869
- Country of Publication:
- United States
- Language:
- English
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