Aiming at the problems of small good workspace, many singular configurations, and limited carrying capacity of non-redundant parallel mechanisms, a full-redundant drive parallel mechanism is designed and developed, and its performance evaluation, good workspace identification, and scale optimization design are studied. First, the kinematics analysis of the planar 6R parallel mechanism is completed. Then, the motion/force transmission performance evaluation index of the mechanism is established, and the singularity analysis of the mechanism is completed. Based on this, the fully redundant driving mode of the mechanism is determined, and the good transmission workspace of the mechanism in this mode is identified. Then, the mapping relationship between the performance and scale of the mechanism is established by using the space model theory, and the scale optimization of the mechanism is completed. Finally, the robot prototype is made according to the optimal scale, and the performance verification is carried out based on the research of dynamics and control strategy. The results show that the fully redundant actuation parallel mechanism obtained by design optimization has high precision and large bearing capacity. The position repeatability and position accuracy are 0.053 mm and 0.635 mm, respectively, and the load weight ratio can reach 15.83%. The research results of this paper complement and improve the performance evaluation and scale optimization system of redundantly actuated parallel mechanisms.

Due to the errors in manufacturing and assembly, there are differences between the actual model and the theoretical model of the robot, which affects the positioning accuracy of the robot end-effector. In order to improve the accuracy of robot end-effector position, a robot error compensation strategy based on error sensitivity is proposed.Firstly, the robot kinematic model is established by Denavit–Hartenberg method, and the sensitivity of end-effector position error is analyzed. According to the influence degree of different kinematic parameters on the robot end-effector position accuracy in the whole workspace, different weights are given to different kinematic parameters. Secondly, the kinematic error model is established, and the redundancy of the error parameter matrix is analyzed to obtain an independent error model. Thirdly, based on the error sensitivity analysis, a weighted Levenberg–Marquard algorithm with adaptive penalty factor is proposed, and the kinematic parameters are iteratively identified. Finally, an error compensation experiment is carried out by using a universal serial six-degree-of-freedom robot. The experimental results show that the maximum error, mean absolute error and root mean square error of the position error on the test set are reduced by 90.75%, 89.86% and 95.64% respectively. The research in this paper provides a theoretical basis for robot end error compensation.

Wheel loaders are often used for material transportation in areas such as mines and construction sites, and their articulated motion characteristics bring great challenges to their path planning and trajectory tracking. Aiming at the problems of long planning path and low tracking accuracy in the path planning of articulated loaders, this paper proposes an improved hybrid A* algorithm based on bidirectional Dubins curve to realize the path planning and trajectory tracking in the process of automatic material transportation of loaders. Firstly, the kinematics model is constructed based on the vehicle size, and the bidirectional Dubins curve combined with hybrid A* algorithm is introduced to improve the forward and backward switching mechanism of the loader, and the path is smoothed by factor graph. Then, the kinematics model is analyzed, and the mapping relationship between navigation point speed and vehicle speed and articulation angle is obtained, and the vehicle state is obtained by sensor feedback. Finally, the vehicle speed and articulation angle are solved by graph optimization. The simulation and field test verify its performance, and the path length is shortened by 17.73% compared with that before optimization. The research results show that the proposed algorithm can accurately control the wheel loader from the initial position to the target position, realize the stable work of the whole vehicle in the work area, and provide technical support for the loader’s autonomous operation.

Articulated heavy-duty robots are more and more widely used in the construction environment. Aiming at the problems of low working efficiency and high energy consumption of this kind of robot, a multi-objective adaptive trajectory planning method combining path optimization and trajectory optimization is proposed to improve the working efficiency of the robot and reduce energy consumption. Firstly, based on kinematics and dynamic analysis considering friction, the energy consumption model of robot trajectory is constructed. Then, according to the posture of the key points in the known workspace, the optimal path points in the joint space are obtained by a path point solution method considering the joint load characteristics. On this basis, a multi-objective model considering running time and energy consumption is established to plan the interpolation trajectory of the joint space of the quintic B-spline curve. Finally, constrained by the velocity, acceleration and torque of the joint of the manipulator, the optimal solution is obtained by using the elite non-dominated sorting genetic algorithm (NSGA-II), and the optimal weight factor is selected by a multi-objective adaptive optimization method to obtain the optimal position-time series. The experimental results show that compared with the quintic polynomial trajectory optimization method, the energy consumption of the proposed method is reduced by 10.90% under the same working efficiency. The research results of this paper provide a new optimization idea for other target trajectory planning.

Aiming at the inherent defects of single-drive mode parallel mechanisms, such as small good workspace and many singular configurations, a new multi-drive mode parallel mechanism is proposed from the perspective of driving innovation. Taking the planar 6R parallel mechanism as an example, the driving layout configuration strategy and scale optimization design are studied. First, the potential driving layout of the mechanism is analyzed, and the inverse kinematics model of the mechanism is established. Then, based on the motion/force transmission index, the singular space and good transmission workspace of the mechanism are identified, and the mechanism-driven layout configuration strategy is formulated to complete the performance comparison analysis. Finally, based on the performance map method, the scale optimization design of the mechanism is carried out, the prototype is developed and manufactured, and the experimental verification is carried out. The research results show that the multi-drive mode parallel mechanism can improve its kinematic performance without changing the topological structure and scale parameters of the mechanism.

To address the demands for precision and load-bearing capacity in the installation of building panels, a hybrid force-position driven robot with redundant actuation has been developed. The mechanical performance of this robot is primarily governed by its central parallel mechanism, which is equipped with redundant actuators matching the degrees of freedom. Non-redundant and redundant actuators are respectively responsible for position and force control. The inclusion of redundant force-driven joints has increased the internal coupling within the mechanism. To enhance the coordination between position and force control, a hybrid synchronized control method based on cross-coupling has been proposed. Initially, kinematic and dynamic models of the parallel structure were established. Under predefined trajectories, the theoretical inputs for each actuator were calculated using inverse kinematics and dynamics. Subsequently, employing the principle of cross-coupling, the torque output from the position actuators was used as feedback. This feedback was processed by a synchronized coordination controller to adjust the output force of the redundant force-driven joints. By adjusting the output force of the redundant actuators, the torque burden on the position actuators was effectively reduced, thereby enhancing the precision of position control. Additionally, under the same load conditions, smaller power actuators could be utilized for position control, reducing the overall weight of the robot and improving its load-to-weight ratio. To validate the effectiveness of the proposed control strategy, a robotic simulation environment was established. The simulation results demonstrated significant reductions in the average torque required by the position actuators across three different trajectories, with reductions of 91.43%, 54.56%, and 80.6% respectively. Finally, the load-bearing capacity and the load-to-weight ratio of the prototype were assessed. Experimental results confirmed that the prototype achieved a load-to-weight ratio of 15.83%, validating the effectiveness of the hybrid synchronized control method based on cross-coupling.