Adaptive Walking Control for a Quadruped Robot on Irregular Terrain Using the Complex-Valued CPG Network

Zhang, Yong; Wang, Hao; Ding, Yi; Hou, Beiping

doi:10.3390/sym13112090

Cited by 5 publications

(2 citation statements)

References 21 publications

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“…For example, extremely steep slopes are still difficult to overcome. Most of the articles test only gentle/mild slopes such as 10 • -20 • (e.g., [50,54,60,75]). A 30 • slope was tested in one paper [60], and a V-shaped walls with 50 • slope is considered in another study [49].…”

Section: Scientific Evidencementioning

confidence: 99%

Legged locomotion over irregular terrains: state of the art of human and robot performance

et al. 2022

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Legged robotic technologies have moved out of the lab to operate in real environments, characterized by a wide variety of unpredictable irregularities and disturbances, all this in close proximity with humans. Demonstrating the ability of current robots to move robustly and reliably in these conditions is becoming essential to prove their safe operation. Here, we report an in-depth literature review aimed at verifying the existence of common or agreed protocols and metrics to test the performance of legged system in realistic environments. We primarily focused on three types of robotic technologies, i.e., hexapods, quadrupeds and bipeds. We also included a comprehensive overview on human locomotion studies, being it often considered the gold standard for performance, and one of the most important sources of bioinspiration for legged machines. We discovered that very few papers have rigorously studied robotic locomotion under irregular terrain conditions. On the contrary, numerous studies have addressed this problem on human gait, being nonetheless of highly heterogeneous nature in terms of experimental design. This lack of agreed methodology makes it challenging for the community to properly assess, compare and predict the performance of existing legged systems in real environments. On the one hand, this work provides a library of methods, metrics and experimental protocols, with a critical analysis on the limitations of the current approaches and future promising directions. On the other hand, it demonstrates the existence of an important lack of benchmarks in the literature, and the possibility of bridging different disciplines, e.g., the human and robotic, towards the definition of standardized procedures that will boost not only the scientific development of better bioinspired solutions, but also their market uptake.

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Section: Scientific Evidencementioning

confidence: 99%

Legged locomotion over irregular terrains: state of the art of human and robot performance

et al. 2022

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“…They achieved trot gait on the baby elephant quadruped robot. In a more recent study by Zhang et al in 2021 [17], a CPG network with complex-value parameters was designed based on the dynamics of the quadruped robot and, additionally, a DC motor was integrated into the CPG network, enabling the robot to perform uphill and downhill motions. Although CPG control has achieved certain results, its coupling is strong and complicated, which has certain restrictions on the robot's movement, and its parameter tuning is also a complicated process.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Locomotion Learning for Quadruped Robots by Combining DRL with a Cosine Oscillator Based Rhythm Controller

Zhang,

Wu,

Wang

et al. 2023

Applied Sciences

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Animals have evolved to adapt to complex and uncertain environments, acquiring locomotion skills for diverse surroundings. To endow a robot’s animal-like locomotion ability, in this paper, we propose a learning algorithm for quadruped robots based on deep reinforcement learning (DRL) and a rhythm controller that is based on a cosine oscillator. For a quadruped robot, two cosine oscillators are utilized at the hip joint and the knee joint of one leg, respectively, and, finally, eight oscillators form the controller to realize the quadruped robot’s locomotion rhythm during moving. The coupling between the cosine oscillators of the rhythm controller is realized by the phase difference, which is simpler and easier to realize when dealing with the complex coupling relationship between different joints. DRL is used to help learn the controller parameters and, in the reward function design, we address the challenge of terrain adaptation without relying on the complex camera-based vision processing but based on the proprioceptive information, where a state estimator is introduced to achieve the robot’s posture and help finally utilize the food-end coordinate. Experiments are carried out in CoppeliaSim, and all of the flat, uphill and downhill conditions are considered. The results show that the robot can successfully accomplish all the above skills and, at the same time, with the reward function designed, the robot’s pitch angle, yaw angle and roll angle are very small, which means that the robot is relatively stable during walking. Then, the robot is transplanted to a new scene; the results show that although the environment is previously unencountered, the robot can still fulfill the task, which demonstrates the effectiveness and robustness of this proposed method.

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Guidance and Control of Underwater Hexapod Robot Based on Adaptive Sliding Mode Strategy

Gong,

Zhang,

et al. 2024

J Bionic Eng

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Adaptive Walking Control for a Quadruped Robot on Irregular Terrain Using the Complex-Valued CPG Network

Cited by 5 publications

References 21 publications

Legged locomotion over irregular terrains: state of the art of human and robot performance

Legged locomotion over irregular terrains: state of the art of human and robot performance

Adaptive Locomotion Learning for Quadruped Robots by Combining DRL with a Cosine Oscillator Based Rhythm Controller

Guidance and Control of Underwater Hexapod Robot Based on Adaptive Sliding Mode Strategy

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