Central Pattern Generator With Inertial Feedback for Stable Locomotion and Climbing in Unstructured Terrain

Sartoretti, Guillaume; Shaw, Samuel; Lam, Katie; Fan, Naixin; Travers, Matthew; Choset, Howie

doi:10.1109/icra.2018.8461013

Cited by 39 publications

(25 citation statements)

References 17 publications

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“…Many efforts have been dedicated to achievie online gait adaptation of legged robots. In previous studies, a robot's stable position was analyzed to apply the kinematics of its step to calculate optimized joint angles for appropriate foot placement [34], [35] and path planning [36]. A similar study was conducted by Focchi et al [14], who applied a torque-controlled technique to determine foot placement and maintain a robot's balance on a high-slope terrain.…”

Section: Discussionmentioning

confidence: 99%

Bio-Inspired Adaptive Locomotion Control System for Online Adaptation of a Walking Robot on Complex Terrains

et al. 2020

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Developing a controller that enables a walking robot to autonomously adapt its locomotion to navigate unknown complex terrains is difficult, and the methods developed to address this problem typically require robot kinematics with arduous parameter tuning or machine learning techniques that require several trials or repetitions. To overcome this limitation, in this paper, we present continuous, online, and self-adaptive locomotion control inspired by biological control systems, including neural control and hormone systems. The control approach integrates our existing modular neural locomotion control (MNLC) and a newly introduced artificial hormone mechanism (AHM). While the MNLC can generate various gaits through its modulatory input, the AHM, which replicates the endocrine system, adapts to rapid changes in online walking frequency and gait in response to different complex terrains. The control approach is evaluated on an insect-like hexapod robot with 18 degrees of freedom. We provide the results in three sections. First, we demonstrate the adaptability of the robot with the proposed artificial hormones. Second, we compare the performance of two robots with and without artificial hormones while walking on different complex terrains using three performance indexes (stability, harmony, and displacement). Third, we evaluate real-time online adaptations in the real world through real robot walking on different unknown terrains. The experimental results demonstrate that the robot with the proposed artificial hormones does not require several learning trials to adapt its locomotion. Instead, it can continuously adapt its locomotion online, thereby providing greater success and higher performance than other techniques when walking on all terrains. INDEX TERMS Adaptive behaviors, artificial hormones, central pattern generators, locomotion control, neural networks, walking machines.

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Section: Discussionmentioning

confidence: 99%

Bio-Inspired Adaptive Locomotion Control System for Online Adaptation of a Walking Robot on Complex Terrains

et al. 2020

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“…For example, a fly could produce inphase rhythms to provide the general control of head-cleaning movements but the sensory feedback from various parts of the head could adjust these movements to optimize the efficiency of cleaning of those parts. The concept of sensory feedback playing a role in stabilizing and adjusting rhythmic behaviors has been explored in robotics (Wang, 2014, Sartoretti, G., 2018 and in walking mice (Mayer W. P., 2018, Santuz, A., 2019, as well as in computational modeling of CPGs (Yu, Z., 2021).…”

Section: Discussionmentioning

confidence: 99%

Behavioral evidence for nested central pattern generator control ofDrosophilagrooming

Ravbar

Zhang

Simpson

2020

Preprint

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Central pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, simplifying control over different time-scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On the short time-scale (5-7 Hz), flies execute periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head cleaning and leg rubbing are also periodic on a longer time-scale (0.3 - 0.6 Hz). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase – a hallmark of CPG control – and also that the two time-scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship also holds when sensory drive is held constant using optogenetic activation, but the rhythms decouple in spontaneously grooming flies, showing that alternative control modes are possible. Nested CPGs simplify generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.

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“…The CPG algorithm has been used to realize the smooth transition between different gaits of the hexapod robot 17,18 and walking under different terrains. 19 Liu and Zhang 20 and Liu et al 21 realize the movement of a quadruped robot in different gaits by using a CPG control network composed of different oscillators. Liu et al 8 and Santos et al 22 applied CPG control strategy to the motion control of the biped robot.…”

Section: Introductionmentioning

confidence: 99%

Motion coordination control of planar 5R parallel quadruped robot based on SCPL-CPG

Chen

Zhang

et al. 2022

Advances in Mechanical Engineering

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The parallel leg of the quadruped robot has good structural stiffness, accurate movement, and strong bearing capacity, but it is complicated to control. To solve this problem, a series connection of parallel legs (SCPL) was proposed, as well as a control strategy combined with the central pattern generator (CPG). With the planar 5R parallel leg as the research object, the SCPL analysis method was used to analyze the leg structure. The topology of CPG network was built with the Hopf oscillator as the unit model, and the CPG was the core to model the robot control system. By continuously adjusting the parameters in the CPG control system and changing the connection weight, and the smooth transition between gaits was realized. The simulation results show that the SCPL analysis method can be effectively used in the analysis of parallel legs, and the control system can realize the smooth transition between gaits, which verifies the feasibility and effectiveness of the proposed control strategy.

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Central Pattern Generator With Inertial Feedback for Stable Locomotion and Climbing in Unstructured Terrain

Cited by 39 publications

References 17 publications

Bio-Inspired Adaptive Locomotion Control System for Online Adaptation of a Walking Robot on Complex Terrains

Bio-Inspired Adaptive Locomotion Control System for Online Adaptation of a Walking Robot on Complex Terrains

Behavioral evidence for nested central pattern generator control ofDrosophilagrooming

Motion coordination control of planar 5R parallel quadruped robot based on SCPL-CPG

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