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Contact-based motion planning for manipulation, object exploration orbalancing often requires finding sequences of fixed and sliding contacts andplanning the transition from one contact in the environment to another.However, most existing algorithms concentrate on the control and learningaspect of sliding contacts, but do not embed the problem into a principledframework to provide guarantees on completeness or optimality. To address thisproblem, we propose a method to extend constraint-based planning using contacttransitions for sliding contacts. Such transitions are elementary operationsrequired for whole contact sequences. To model sliding contacts, we define asliding contact constraint that permits the robot to slide on the surface of amesh-based object. To exploit transitions between sliding contacts, we developa contact transition sampler, which uses three constraint modes: contact with astart surface, no contact and contact with a goal surface. We sample thesetransition modes uniformly which makes them usable with sampling-based planningalgorithms. Our method is evaluated by testing it on manipulator arms of two,three and seven internal degrees of freedom with different objects and varioussampling-based planning algorithms. This demonstrates that sliding contactconstraints could be used as an elementary method for planning long-horizoncontact sequences for high-dimensional robotic systems.

Efficient Sampling of Transition Constraints for Motion Planning under Sliding Contacts