Abundant Computer and Robot Experiments Verifying Minimum Joint Motion Planning and Control of Redundant Arms via Zhang Neural Network

In recent years, the robotics industry has been a hotspot and provided much convenience in people's daily life. For further research on robots, we introduce the problem of velocity-level minimum joint motion planning and control in this paper. Firstly, by using the Zhang neural network (ZNN) method and the Lagrange multiplier method, a continuous-time ZNN model is presented to solve the problem. Besides, an advanced ten-instant time-discretization formula with higher precision is presented, and five discrete-time ZNN (DTZNN) models are listed because of the digital hardware's requirements. At last, computer and robot experiments verify the effectiveness and feasibility of the presented DTZNN models.