TOP: Time Optimization Policy for Stable and Accurate Standing Manipulation with Humanoid Robots

-- Humanoid robots have the potential capability to perform a diverse range of manipulation tasks, but this is based on a robust and precise standing controller . Existing methods are either ill-suited to precisely control high-dimensional upper-body joints, or difficult to ensure both robustness and accuracy, especially when upper-body motions are fast. This paper proposes a novel time optimization policy (TOP), to train a standing manipulation control model that ensures balance, precision, and time efficiency simultaneously, with the idea of adjusting the time trajectory of upper-body motions but not only strengthening the disturbance resistance of the lower-body. Our approach consists of three parts. Firstly, we utilize motion prior to represent upper-body motions to enhance the coordination ability between the upper and lower-body by training a variational autoencoder (V AE). Then we decouple the whole-body control into an upper-body PD controller for precision and a lower-body RL controller to enhance robust stability. Finally, we train TOP method in conjunction with the decoupled controller and V AE to reduce the balance burden resulting from fast upper-body motions that would destabilize the robot and exceed the capabilities of the lower-body RL policy. The effectiveness of the proposed approach is evaluated via both simulation and real world experiments, which demonstrate the superiority on standing manipulation tasks stably and accurately. The project page can be found at https://anonymous.4open.science/w/top-258F/. I. INTRODUCTION Humanoid robots are the most potential embodied agents for the purpose of liberating human-level labors, as they are designed to perform anthropomorphic motions and various whole-body loco-manipulation tasks, including industrial parts assembly, home service, etc.[1]. Their anthropomorphism naturally makes them more suitable than other specific robots to interact with environments, objects and humans to complete various physical tasks. Although rapid growth has been achieved in the field of humanoid robots[2], it remains a challenge to execute various intricate tasks while maintaining balance and precision simultaneously due to the intrinsic instability characteristic of humanoid robot. Existing methods can be broadly divided into two paradigms: whole-body controllers[3, 4, 5] and upper and lower-body decoupled controllers[6, 7]. Rong Xiong is the corresponding author.