A Repeatable Optimization for Kinematic Energy System with Its Mobile Manipulator Application

Abstract

For repeatable motion of redundant mobile manipulators, the flexible base platform and the redundant manipulator have to be returned to the desired initial position simultaneously after completing the given tasks. To remedy deviations between initial position and desired position of each kinematic joint angle, a special kind of repeatable optimization for kinematic energy minimization based on terminal-time Zhang neural network (TTZNN) with finite-time convergence is proposed for inverse kinematics of mobile manipulators. It takes the advantages that each joint of the manipulator is required to return to the desired initial position not considering the initial orientation of itself for realizing repeatable kinematics control. Unlike the existed training methods, such an optimization of kinematic energy scheme based on TTZNN can not only reduce the convergent position error of each joint to zero in finite time, but also improve the convergent precision. Theoretical analysis and verifications show that the proposed optimal kinematic energy scheme accelerates the convergent rate, which is tended to be applied in practical robot kinematics. Simulation results on the manipulator with three mobile wheels substantiate the timeliness and repetitiveness of the proposed optimization scheme.

A Gradient-Based Recurrent Neural Network for Visual Servoing of Robot Manipulators with Acceleration Command

“…Owing to the derivative process that GRNN (26) originates from the error function ( 17), the gradient descent formula is designed to reduce the image error, thus ultimately achieving equality constraint (13). In the next place, the output control command is established at the acceleration level, which corresponds to the acceleration-level kinematics formula (12). Note that compensation item ϖ is the pseudoinverse solution of the system function in a stable state, i.e., the minimization of joint acceleration, which is equivalent to minimizing objective function (11).…”

“…In current years, the kinematic control of redundant robots has become a research hotspot, thus drawing the attention of abundant scholars to expand their applications [12][13][14][15][16]. Zhang and Zhang present a minimum-velocity-norm (MVN) scheme for redundancy resolution of the redundant manipulators, which retains the robot joints within safe bounds [17].…”

Master‐Slave Composite Vibration Control of a Mobile Flexible Manipulator via Synchronization Optimization of Observation and Feedback

“…According to the assumed mode method [24,25], the displacement of P point on the flexible manipulator can be expressed as 2 Complexity…”

“…Under the drive of the servomotors, the mobile manipulator can realize di erent industrial operations according to the design requirements. us, it is widely used in precision assembly, welding, handling, and other industrial occasions [1][2][3]. At present, the obvious disadvantage of the robot mobile manipulator system is its heavy structure.…”

Control of Trajectory Tracking for Mobile Manipulator Robot with Kinematic Limitations and Self-Collision Avoidance

“…Therefore, these methods do not need to solve the inverse matrix, which can improve the solution success rate and reduce the difficulty of programming [20]; however, significant errors near singular locations cannot be avoided, and it may not be possible to determine the suitable speeds to meet the physical constraints of the driving motors. In a neural network method [21,22], the non-linear relationship between the driving joints and the end effector's position was directly determined through training on large data sets. This process is complicated and may require a very long time.…”