Abstract:

The main objective of this thesis is to develop an autonomous navigation system for a mobile manipulator for grasping tasks, which can operate in a complex environment. A high-dimensional planning algorithm for a robot to grasp or manipulate an object is developed. First, we generate a set of feasible grasps for a given object. We consider a grasp’s stability (force-closure) and local environment clearance to form a scoring function to generate feasible grasps that are the goals in grasp planning.

Next, in order solve the planning problems that have different dimensions in the configuration space and the goal space, we propose a BiRRT-GCS (Bi-directional RRT with Goal Configuration Search) algorithm, which can make the robot move toward the object and use its arm to reach the goal without using inverse kinematics in a known environment. Moreover, the algorithm is more than five times faster than the BiSpace algorithm in complex scenes. We also propose a Multi-Goal BiRRT-GCS planner to increase the probability of success of a grasping task. The simulation results and the real world experiment show that our algorithms can efficiently find a trajectory of the robot to accomplish grasping tasks.