TOCALib: Optimal Control Library with Interpolation for Bimanual Manipulation and Obstacles Avoidance
Yulia Danik, Dmitry Makarov, Aleksandra Arkhipova, Sergei Davidenko, Aleksandr Panov
Abstract
The paper presents a new approach for constructing a library of optimal trajectories for two robotic manipulators, Two-Arm Optimal Control and Avoidance Library (TOCALib). The optimization takes into account kinodynamic and other constraints within the FROST framework. The novelty of the method lies in the consideration of collisions using the DCOL method, which allows obtaining symbolic expressions for assessing the presence of collisions and using them in gradient-based optimization control methods. The proposed approach is applicable for complex bimanual manipulations that require precision. In this paper we tested TOCALib on Mobile Aloha robot, as an example. The approach can be extended to other bimanual robots, as well as to gait control of bipedal robots. It can also be used to construct training data for machine learning tasks for manipulation.