The existing dynamic path planning algorithm cannot properly solve the problem of the path planning of wheeled robot on the slope ground with dynamic moving obstacles. To solve the problem of slow convergence rate in the training phase of DDQN, the dynamic path planning algorithm based on Tree-Double Deep Q Network (TDDQN) is proposed. The algorithm discards detected incomplete and over-detected paths by optimizing the tree structure, and combines the DDQN method with the tree structure method. Firstly, DDQN algorithm is used to select the best action in the current state after performing fewer actions, so as to obtain the candidate path that meets the conditions. And then, according to the obtained state, the above process is repeatedly executed to form multiple paths of the tree structure. Finally, the non-maximum suppression method is used to select the best path from the plurality of eligible candidate paths. ROS simulation and experiment verify that the wheeled robot can reach the target effectively on the slope ground with moving obstacles. The results show that compared with DDQN algorithm, TDDQN has the advantages of fast convergence and low loss function.
Purpose The gait planning and control of quadruped crawling robot affect the stability of the robot walking on a slope. The control includes the position control in the swing phase, the force control in the support phase and the switching control in the force/position switching. To improve the passing ability of quadruped crawling robot on a slope, this paper aims to propose a soft control strategy. Design/methodology/approach The strategy adopts the statically stable crawling gait as the main gait. As the robot moves forward, the position/force section switching control is adopted. When the foot does not touch the ground, the joint position control based on the variable speed PID is performed. When the foot touches the ground, the position-based impedance control is performed, and a fuzzy multi-model switching control based on friction compensation is proposed to achieve smooth switching of force and position. Findings The proposed method offers a solution for stable passage in slope environment. The quadruped crawling robot can realize smooth switching of force/position, precise positioning in the swing process and soft control of force in the supporting phase. This fact is verified by simulation and test. Originality/value The method presented in this paper takes advantage of minimal tracking errors and minimal jitters. Simulations and tests were performed to evaluate the performance.
Purpose Aiming at the problem that quadruped crawling robot is easy to collide and overturn when facing obstacles and bulges in the process of complex slope movement, this paper aims to propose an obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition. Design/methodology/approach First, considering the problem of low uniformity of feature points in terrain recognition images under complex slopes, which leads to too long feature point extraction time, an improved ORB (Oriented FAST and Rotated BRIEF) feature point extraction method is proposed; second, when the robot avoids obstacles or climbs over bumps, aiming at the problem that the robustness of a single step cannot satisfy the above two motions at the same time, the crawling gait is planned according to the complex slope terrain, and a robot obstacle avoidance gait planning based on the artificial potential field method is proposed. Finally, the slope walking experiment is carried out in the Robot Operating System. Findings The proposed method provides a solution for the efficient walking of robot under slope. The experimental results show that the extraction time of the improved ORB extraction algorithm is 12.61% less than the original ORB extraction algorithm. The vibration amplitude of the robot’s centroid motion curve is significantly reduced, and the contact force is reduced by 7.76%. The time it takes for the foot contact force to stabilize has been shortened by 0.25 s. This fact is verified by simulation and test. Originality/value The method proposed in this paper uses the improved feature point recognition algorithm and obstacle avoidance gait planning to realize the efficient walking of quadruped crawling robot on the slope. The walking stability of quadruped crawling robot is tested by prototype.
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