International audienceWe present a planner for underactuated hyper-redundant robots, such as humanoid robots, for which the movement can only be initiated by taking contacts with the environment. We synthesize our previous work on the subject and go further into details to give an in-depth description of the contact planning problem and the mechanisms of our contact planner. We highlight the structure of the problem with a simple example, present the contact space and the heuristics we use for planning, and explain thoroughly the implementation of the different parts of the planner. Finally we give examples of planning results for complex scenarios with the humanoid robot HRP-2
(JRL) adrien(dot)escande(at)ensmp.fr, kheddar(at)ieee.org, sylvain(dot)miossec(at)aist.go.jp, sylvain(dot)garsault(at)aist.go.jp Summary. This paper presents improvements in contact-before-motion planning for humanoid robots that enables to find a path in very constrained environments. Starting from our previous work, the main novelties are to use a rough trajectory to drive the search and as a criterion to find new contacts and generate the best nodes first. This way only few nodes are effectively explored, speeding up the planning process. We experience the algorithm on the real humanoid HRP-2 in a complex scenario.
This paper deals with the motion planning of a poly-articulated robotic system for which support contacts are allowed to occur between any part of the body and any part of the environment. Starting with a description of the environment and of a target, it computes a sequence of postures that allow our system to reach its target. We describe a very generic architecture of this planner, highly modular, as well as a first implementation of it. We then present our results, both simulations and real experiments, for a simple grasping task using the HRP-2 humanoid robot.
This paper proposes a real-time implementation of collision and self-collision avoidance for robots. On the basis of a new proximity distance computation method which ensures having continuous gradient, a new controller in the velocity domain is proposed. The gradient continuity encompasses no jump in the generated command. Included in a stack of tasks architecture, this controller has been implemented on the humanoid platform HRP-2 and experienced in a grasping task while walking and avoiding collisions with the environment and auto-collisions. Index Terms-stack of tasks, proximity distance with continuous gradient, self-collision and obstacle collisions avoidance.
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