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We consider the problem of planning a collision-free path for ahigh-dimensional robot. Specifically, we suggest a planning framework where amotion-planning algorithm can obtain guidance from a user. In contrast toexisting approaches that try to speed up planning by incorporating experiencesor demonstrations ahead of planning, we suggest to seek user guidance only whenthe planner identifies that it ceases to make significant progress towards thegoal. Guidance is provided in the form of an intermediate configuration$\hat{q}$, which is used to bias the planner to go through $\hat{q}$. Wedemonstrate our approach for the case where the planning algorithm isMulti-Heuristic A* (MHA*) and the robot is a 34-DOF humanoid. We show that ourapproach allows to compute highly-constrained paths with little domainknowledge. Without our approach, solving such problems requirescarefully-crafting domain-dependent heuristics.

Online, interactive user guidance for high-dimensional, constrained motion planning