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Towards Robot Task Planning From Probabilistic Models of Human Skills
[article]
2016
arXiv
pre-print
We describe an algorithm for motion planning based on expert demonstrations of a skill. In order to teach robots to perform complex object manipulation tasks that can generalize robustly to new environments, we must (1) learn a representation of the effects of a task and (2) find an optimal trajectory that will reproduce these effects in a new environment. We represent robot skills in terms of a probability distribution over features learned from multiple expert demonstrations. When utilizing a
arXiv:1602.04754v1
fatcat:gjjv4z6ybjg2dcknt3bqcyzkxq