Object Placement Planning and optimization for Robot Manipulators We address the problem of planning the placement of a rigid object with a dualarm robot in a cluttered environment. In this task, we need to locate a collisionfree pose for the object that a) facilitates the stable placement of the object, b) is reachable by the robot and c) optimizes a usergiven placement objective. In addition, we need to select which robot arm to perform the placement with. To solve this task, we propose an anytime algorithm that integrates samplingbased motion planning with a novel hierarchical search for suitable placement poses. Our algorithm incrementally produces approach motions to stable placement poses, reaching placements with better objective as runtime progresses. We evaluate our approach for two different placement objectives, and observe its effectiveness even in challenging scenarios.

Dualarm Assembly Planning Considering Gravitational Constraints Planning dualarm assembly of more than three objects is a challenging Task and Motion Planning (TAMP) problem. The assembly planner shall consider not only the pose constraints of objects and robots, but also the gravitational constraints that may break the finished part. This paper proposes a planner to plan the dualarm assembly of more than three objects. It automatically generates the grasp configurations and assembly poses, and simultaneously searches and backtracks the grasp space and assembly space to accelerate the motion planning of robot arms. Meanwhile, the proposed method considers gravitational constraints during robot motion planning to avoid breaking the finished part. In the experiments and analysis section, the time cost of each process and the influence of different parameters used in the proposed planner are compared and analyzed. The optimal values are used to perform realworld executions of various robotic assembly tasks. The planner is proved to be robust and efficient through the experiments.