IET Cybersystems and Robotics最新文献

Compared with the traditional manipulator, the hyper-redundant manipulator has the advantage of high flexibility, which is particularly suitable for all kinds of complex working environments. However, the complex space environment requires the hyper-redundant manipulator to have stronger obstacle avoidance ability and adaptability. In order to solve the problems of a large amount of calculation and poor obstacle avoidance effects in the path planning of the hyper-redundant manipulator, this paper introduces the ‘backbone curve’ approach, which transforms the problem of solving joint path points into the behaviour of determining the backbone curve. After the backbone curve approach is used to design the curve that meets the requirements of obstacle avoidance and the end pose, the least squares fitting and the improved space joint fitting are used to match the plane curve and the space curve respectively, and the angle value of each joint of the manipulator is limited by the algorithm. Furthermore, a fusion obstacle avoidance algorithm is proposed to obtain the joint path points of the hyper-redundant manipulator. Compared with the classic Jacobian iteration method, this method can avoid obstacles better, has the advantages of simple calculation, high efficiency, and can fully reflect the geometric characteristics of the manipulator. Simulation experiments have proven the feasibility of the algorithm.

To address complex work conditions incredibly challenging to the stability of power line inspection robots, we design a walking mechanism and propose a variable universe fuzzy control (VUFC) method based on multi-work conditions for flying-walking power line inspection robots (FPLIRs). The contributions of this paper are as follows: (1) A flexible pressing component is designed to improve the adaptability of the FPLIR to the ground line slope. (2) The influence of multi-work conditions on the FPLIR's walking stability is quantified using three condition parameters (i.e., slope, slipping degree and swing angle), and their measurement methods are proposed. (3) The VUFC method based on the condition parameters is proposed to improve the walking stability of the FPLIR. Finally, the effect of the VUFC method on walking stability of the FPLIR is teste. The experimental results show that the maximum climbing angle of the FPLIR reaches 29.1°. Compared with the constant pressing force of 30 N, the average value of slipping degree is 0.93°, increasing by 35%. The maximum and average values of robot's swing angle are reduced by 46% and 54%, respectively. By comparing with fuzzy control, the VUFC can provide a more reasonable pressing force while maintaining the walking stability of the FPLIR. The proposed walking mechanism and the VUFC method significantly improve the stability of the FPLIR, providing a reference for structural designs and stability controls of inspection robots.

Tracking control has been a vital research topic in robotics. This paper presents a novel hybrid control strategy for an unmanned underwater vehicle (UUV) based on a bioinspired neural dynamics model. An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods. Then, a novel sliding mode control is proposed, which is capable of providing smooth and continuous torque commands free from chattering. In comparative studies, the proposed combined hybrid control strategy has ensured control signal smoothness, which is critical in real-world applications, especially for a UUV that needs to operate in complex underwater environments.