A real-time explicit mapping and teleoperation control method for humanoid robots with posture constraints

Abstract

In most industrial robot applications, on-site robot operation is required. However, this is not feasible for certain harsh operating conditions, such as high temperatures and intense radiation. In such instances, teleoperation based on machine vision can be applied, and adding posture constraints helps control the robot to complete more complex tasks. The general idea is to use quadratic programming or other optimization methods to solve the problem. In order to improve accuracy and ensure real-time performance, a real-time explicit mapping and teleoperation control (REMTC) is proposed. Based on the principle of "included angle minimization" (IAM), the incorrect mapping problem which might be caused by the traditional method is solved. In addition, considering that the analytical inverse solution algorithm is not as universal as the general optimization framework, an improved structure transformation method is proposed, so that the algorithm can be applied to both Spherical- Revolute-Spherical (SRS) and non-SRS robots. Finally, the experiment verifies the effectiveness of the algorithm in real-time performance, accuracy and reliability.