An opportunistic strategy for motion planning in the presence of soft task constraints

Consider the problem of planning collision-free motions for a robot that is assigned a soft task constraint, i.e., a desired path in task space with an associated error tolerance. To this end, we propose an opportunistic planning strategy in which two subplanners take turns in generating motions. The hard planner guarantees exact realization of the desired task path until an obstruction is detected in configuration space; at this point, it invokes the soft planner, which is in charge of exploiting the available task tolerance to bypass the obstruction and returning control to the hard planner as soon as possible. As a result, the robot will perform the desired task for as long as possible, and deviate from it only when strictly needed to avoid a collision. We present several planning experiments performed in V-REP for the PR2 mobile manipulator in order to show the effectiveness of the proposed planner.