Manipulator Motion Planning for Part Pickup and Transport Operations From a Moving Base

IEEE Transactions on Automation Science and Engineering · 2020 · 72 citations

• Computer Science
• Artificial Intelligence
• Computer Science

Mobile manipulators are being deployed for transporting parts between machines and work stations in warehouses and shop floors. To increase the efficiency of operations, these mobile manipulators are required to complete the tasks as fast as possible. Picking up parts with the manipulator while the mobile base is moving decreases the time required to complete the transportation task and increases the efficiency of operations. However, motions of the manipulator on a moving platform can be risky, and hence, it is desired that the manipulator starts and ends its motions as close as possible to the part being picked up. In this article, we present a bidirectional sampling-based scheme for generating such manipulator trajectories for a given mobile base trajectory for pickup and transportation. Our approach implicitly determines the location of the mobile base where the manipulator motion starts and ends as well as where grasping happens. It also determines which grasping pose to use for picking up the part. Furthermore, we have presented the techniques to reduce the manipulator motion time (span time) and the computation time. Our approach enables us to reduce span time on average by 35% with a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$16\times $ </tex-math></inline-formula> reduction in the computation time compared to the RRT-based baseline methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Transportation of objects is a crucial application in industrial and warehouse environments. Conveyor belts and AGVs are typically used for such applications as they provide an efficient mode of transportation of a large number of objects. However, they may not provide the flexibility which mobile manipulators bring in for small-scale operations. The method presented in this article provides a way to increase the efficiency of operation for mobile manipulators for transportation tasks. We attempt to reduce the risks of the manipulator colliding with expensive equipment and moving obstacles by making sure that the manipulator moves only when needed for picking up objects. Moreover, the method can be used to pick up and transport a variety of parts in different ways using a two-fingered gripper. The method can also easily incorporate different types of grippers and mobile platforms.

Automated planning for robotic layup of composite prepreg

Robotics and Computer-Integrated Manufacturing · 2020 · 55 citations

• Computer Science
• Computer Science
• Artificial Intelligence