Co-Optimization of Tool Orientations, Kinematic Redundancy, and Waypoint Timing for Robot-Assisted Manufacturing

In this paper, we present a concurrent and scalable trajectory optimization method to improve the quality of robot-assisted manufacturing. Our method simultaneously optimizes tool orientations, kinematic redundancy, and waypoint timing on input toolpaths with large numbers of waypoints to improve kinematic smoothness while incorporating manufacturing constraints. Differently, existing methods always determine them in a decoupled manner. To deal with the large number of waypoints on a toolpath, we propose a decomposition-based numerical scheme to optimize the trajectory in an out-of-core manner, which can also run in parallel to improve the efficiency. Simulations and physical experiments have been conducted to demonstrate the performance of our method in examples of robot-assisted additive manufacturing. Note to Practitioners—In robot-assisted manufacturing, how to determine the motion commands according to a sequence of waypoints is a typical problem to be solved where the waypoints represent the positions of a tool-tip. Factors in three aspects need to be planned at each waypoint, including the tool orientation, the tool speed and the redundant degrees-of-freedom on the robotic system. In the trajectory planning step, the objective is always defined as improving the kinematic performance of joint motion in terms of velocity, acceleration, and jerk. Taking the strategy of existing methods that consider these aspects separately will generate less optimal results. This paper presents a new formulation that optimizes all these together while assigning certain manufacturing constraints. Considering that a toolpath can consist of a large number of waypoints in practice, how to improve planning efficiency with limited computer memory is an important issue to be solved. A decomposition based numerical scheme is developed to tackle this problem. The aforementioned issues can be effectively solved by the method proposed in this paper, the performance of which has been demonstrated on a dual robotic system with 6+2 DoFs. The proposed method is general and can also be applied to other types of systems with single or multiple robots as well as other manufacturing methods (e.g. milling).