Gait planning and control of quadruped crawling robot on a slope

Wang, Peng; Song, Chunxiao; Li, Xiaoqiang; Luo, Peng

doi:10.1108/ir-05-2019-0115

Cited by 6 publications

(6 citation statements)

References 8 publications

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“…According to the 3D point cloud information obtained by the camera to judge the road ahead, if the front is flat slope topography, the forward strategy is adopted (you can walk according to the original trajectory), and the trot gait with the duty cycle b > 0.5 is used (Wang et al, 2020). The sequence diagram is shown in Figure 14, where ‹ represents the left front leg, › represents the right front leg, fi represents the right hind leg and fl represents the left hind leg.…”

Section: Trot Gait Planningmentioning

confidence: 99%

Research on obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition

Wang

Song

Renquan

et al. 2022

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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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Section: Trot Gait Planningmentioning

confidence: 99%

Research on obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition

Wang

Song

Renquan

et al. 2022

Self Cite

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“…The method was verified by simulation as an effective attitude position adjustment strategy. A position/ force switching control strategy was proposed by Wang et al (2020) When the foot is not in contact with the ground, the joint position control based on variable speed PID is performed; when the foot is in contact with the ground, the position-based impedance control is performed.…”

Section: Introductionmentioning

confidence: 99%

Research on force/position switching control of servo actuator for hydraulically driven joint robot

Gao,

Wang,

Han

et al. 2024

Transactions of the Institute of Measurement and Control

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According to the robot’s walking motion characteristics, the position/force switching control is studied to realize the segmental control of the robot stroke. This stroke is controlled by position when the foot end of the robot descends from the suspension to the ground. To avoid excessive contact force when the robot touches the ground, force control is carried out when the foot touches the ground. Due to the force and position control methods and control parameters of the hydraulic quadruped robots are different, the precise mathematical model for the joint position control and joint force control of the leg joints of the hydraulic quadruped robot is established using the system identification method. A fuzzy multi-model switching algorithm is proposed to solve the problem of jumping and jitter of system parameters in the process of force/position switching. Through simulation and prototype experiments, fuzzy multi-model switching is compared with direct switching and multi-model switching, and the switching effect of the algorithm is verified.

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Section: Introductionmentioning

confidence: 99%

“…Various methods, including gait planning [6][7][8], trajectory planning [9,10], and reinforcement learning [11][12][13][14][15], have been used to enhance the control of four-legged robots. Wang et al proposed a soft gait control strategy that minimized tracking error and jitter to improve the quadrupedal crawling robot's stable passage in a sidehill environment [6]. Li et al proposed a gait-switching control method for quadrupedal robots based on the combination of dynamic and static and improved the robot's ability to adapt to different terrains using Matlab-Adams co-simulation [7].…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Minimization of Quadruped Robot Based on Reinforcement Learning of DDPG Algorithm

Yan,

Ji,

Chang

2024

Actuators

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Energy consumption is one of the most critical factors in determining the kinematic performance of quadruped robots. However, existing research methods often encounter challenges in quickly and efficiently reducing the energy consumption associated with quadrupedal robotic locomotion. In this paper, the deep deterministic policy gradient (DDPG) algorithm was used to optimize the energy consumption of the Cyber Dog quadruped robot. Firstly, the kinematic and energy consumption models of the robot were established. Secondly, energy consumption was optimized by reinforcement learning using the DDPG algorithm. The optimized plantar trajectory was then compared with two common plantar trajectories in simulation experiments, with the same period and the number of synchronizations but varying velocities. Lastly, real experiments were conducted using a prototype machine to validate the simulation data. The analysis results show that, under the same conditions, the proposed method can reduce energy consumption by 7~9% compared with the existing optimal trajectory methods.

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Gait planning and control of quadruped crawling robot on a slope

Cited by 6 publications

References 8 publications

Research on obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition

Research on obstacle avoidance gait planning of quadruped crawling robot based on slope terrain recognition

Research on force/position switching control of servo actuator for hydraulically driven joint robot

Energy Consumption Minimization of Quadruped Robot Based on Reinforcement Learning of DDPG Algorithm

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