A Pre-Grasping Motion Planning Method Based on Improved Artificial Potential Field for Continuum Robots.

Secure and reliable active debris removal methods are crucial for maintaining the stability of the space environment. Continuum robots, with their hyper-redundant degrees of freedom, offer the ability to capture targets of varying sizes and shapes through whole-arm grasping, making them well-suited for active debris removal missions. This paper proposes a pre-grasping motion planning method for continuum robots based on an improved artificial potential field to restrict the movement area of the grasping target and prevent its escape during the pre-grasping phase. The analysis of the grasping workspace ensures that the target is within the workspace when starting the pre-grasping motion planning by dividing the continuum robot into delivery and grasping segments. An improved artificial potential field is proposed to guide the continuum robot in surrounding the target and creating a grasping area. Specifically, the improved artificial potential field consists of a spatial rotating potential field, an attractive potential field incorporating position and posture potential fields, and a repulsive potential field. The simulation results demonstrate the effectiveness of the proposed method. A comparison of motion planning results between methods that disregard and consider the posture potential field shows that the inclusion of the posture potential field improves the performance of pre-grasping motion planning for spatial targets, achieving a success rate of up to 97.8%.

TeCVP: A Time-Efficient Control Method for a Hexapod Wheel-Legged Robot Based on Velocity Planning.

Addressing the problem that control methods of wheel-legged robots for future Mars exploration missions are too complex, a time-efficient control method based on velocity planning for a hexapod wheel-legged robot is proposed in this paper, which is named time-efficient control based on velocity planning (TeCVP). When the foot end or wheel at knee comes into contact with the ground, the desired velocity of the foot end or knee is transformed according to the velocity transformation of the rigid body from the desired velocity of the torso which is obtained by the deviation of torso position and posture. Furthermore, the torques of joints can be obtained by impedance control. When suspended, the leg is regarded as a system consisting of a virtual spring and a virtual damper to realize control of legs in the swing phase. In addition, leg sequences of switching motion between wheeled configuration and legged configuration are planned. According to a complexity analysis, velocity planning control has lower time complexity and less times of multiplication and addition compared with virtual model control. In addition, simulations show that velocity planning control can realize stable periodic gait motion, wheel-leg switching motion and wheeled motion and the operation time of velocity planning control is about 33.89% less than that of virtual model control, which promises a great prospect for velocity planning control in future planetary exploration missions.

Design and optimization of wall-climbing robot impeller by genetic algorithm based on computational fluid dynamics and kriging model.

In recent years, wall-climbing robots have begun to replace manual work at heights to reduce economic losses and casualties caused by working at heights. This paper designs a negative pressure adsorption type wall-climbing robot and analyzes the internal fluid movement state of its negative pressure device and the force analysis of the robot when it is adsorbed and balanced. Furthermore, through the experimental prototype, the influence of wall material, robot pose, negative pressure cavity shape and sealing method on the adsorption performance of the wall-climbing robot is explored. The computational fluid dynamics simulation (CFD) simulation method and experimental results are used to verify each other, which proves the correctness of the simulation results. Based on the Kriging surrogate model, the functional relationship between the impeller blade outlet angle, the impeller inlet diameter, the number of blades as the design variables, the negative pressure as the dependent variable was established, and the genetic algorithm (GA) was used to optimize it. Compared with the original design, the optimized design results of impeller parameters have increased the negative pressure value from 3534.75 to 4491.19 Pa, an increase of 27.06%.