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Manipulation Planning with Multimodal End Point Optimization for Obtaining Multiple Solutions

Motion planning for robotics manipulation is an essential component for automating various tasks. In this study we discuss optimization-based motion planning methods for robotic manipulation. The optimization-based method can compute smooth and collision-free trajectories with relatively short computational cost. Although existing methods are often designed to output a single solution, the objective function is often multimodal and there exist multiple solutions to achieve a given task. On such a task, obtaining multiple solutions gives a user an opportunity to choose one of the solutions based on factors which are not encoded in the objective function. To address this issue, we propose a motion planning framework that ﬁnds multiple solutions. The proposed method is validated in simulated environments with a four-link manipulator in 2D space and a 6 DoFs manipualtor in 3D space.