Adaptive locomotion control of hexapod walking robot for traversing rough terrains with position feedback only

Faigl, Jan; Čížek, Petr

doi:10.1016/j.robot.2019.03.008

Cited by 60 publications

(60 citation statements)

References 22 publications

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“…The proposed mistiming detector is deployed on the hexapod walking robot shown in Figure 6 , a six-legged robot where each leg is formed from three Dynamixel AX-12 servomotors (Faigl and Čížek, 2019 ). In this work, we control two servo motors per leg: the body-coxa and coxa-femur joint servomotors; the third servomotor, femur-tibia joint, is set to a static angle.…”

Section: Deployment and Empirical Validationmentioning

confidence: 99%

Self-Learning Event Mistiming Detector Based on Central Pattern Generator

2021

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A repetitive movement pattern of many animals, a gait, is controlled by the Central Pattern Generator (CPG), providing rhythmic control synchronous to the sensed environment. As a rhythmic signal generator, the CPG can control the motion phase of biomimetic legged robots without feedback. The CPG can also act in sensory synchronization, where it can be utilized as a sensory phase estimator. Direct use of the CPG as the estimator is not common, and there is little research done on its utilization in the phase estimation. Generally, the sensory estimation augments the sensory feedback information, and motion irregularities can reveal from comparing measurements with the estimation. In this work, we study the CPG in the context of phase irregularity detection, where the timing of sensory events is disturbed. We propose a novel self-supervised method for learning mistiming detection, where the neural detector is trained by dynamic Hebbian-like rules during the robot walking. The proposed detector is composed of three neural components: (i) the CPG providing phase estimation, (ii) Radial Basis Function neuron anticipating the sensory event, and (iii) Leaky Integrate-and-Fire neuron detecting the sensory mistiming. The detector is integrated with the CPG-based gait controller. The mistiming detection triggers two reflexes: the elevator reflex, which avoids an obstacle, and the search reflex, which grasps a missing foothold. The proposed controller is deployed and trained on a hexapod walking robot to demonstrate the mistiming detection in real locomotion. The trained system has been examined in the controlled laboratory experiment and real field deployment in the Bull Rock cave system, where the robot utilized mistiming detection to negotiate the unstructured and slippery subterranean environment.

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Section: Deployment and Empirical Validationmentioning

confidence: 99%

Self-Learning Event Mistiming Detector Based on Central Pattern Generator

2021

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“…Repeated simulations are conducted with different predefined CoMs, and the variances of the estimation results are collected for one minute in the convergence horizon. The fivenumber summary [27] is visualized in Fig. 7.…”

Section: B Reliability Analysismentioning

confidence: 99%

Locomotion Control of Quadruped Robots With Online Center of Mass Adaptation and Payload Identification

Ding

Zhou

et al. 2020

IEEE Access

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“…Zhang et al [7] and Yin et al [8] improved the motion continuity and stability of the quadruped robot through reasonable planning of its gait. Faigl et al [9] designed an adaptive motion controller applied to a hexapod robot, which can accurately detect the contact points between the legs and the ground, so that the hexapod robot can walk on rough terrain.…”

Section: Introduction mentioning

confidence: 99%

Design of bionic goat quadruped robot mechanism and walking gait planning

Zhang¹,

Chen²,

Guo³

et al. 2020

International Journal of Agricultural and Biological Engineering

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In order to improve the walking stability and obstacle jumping ability of the robot on the slope, the goat was taken as the bionic prototype, a kind of bionic goat quadruped robot has been designed. By the bionic principle, the mechanical structure of the quadruped robot was designed, and the Denavit-Hartenberg (D-H) method was used to build the kinematic model, through which the forward and inverse kinematics of the robot was calculated, thus the equations of velocity and acceleration of the joint angle change were obtained during the quadruped robot motion, providing control theory foundation for robots. During walk gait planning, a low contact compact foot trajectory planning method using a high order polynomial curve was used to carry out the foot trajectory planning of the robot for the swing phase and stance phase. Through MATLAB software simulation, the simulation results of MATLAB software showed that the trajectory of the foot of the quadruped robot was semi-elliptic in a gait cycle, which were basically consistent with the foot trajectory obtained from the previous goat slope walking test. Therefore, the simulation results by MATLAB software showed that the foot trajectory was reasonable. Based on this, a gait plan was carried out, and the sequence of the lift leg steps of the robot was obtained. The test platform for the whole machine was built. The results showed that the height of the leg of the quadruped robot was 7.37 cm, and the length of the gait was 28.40 cm. Compared with the planned average gait length S=30 cm and average step height H=7 cm, the error of the leg height and the gait length was 5.28% and 5.33%, respectively. The designed gait planning achieved the expected results. The knee joint angle varied from 126.3° to 156.1°, and the hip joint angle varied from 103.9° to 138.4°. The changes in the joint angle of the quadruped robot could prove the correctness of the foot motion trajectory planning, which will provide a theoretical basis for the structural design and gait planning of the quadruped robot.

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Adaptive locomotion control of hexapod walking robot for traversing rough terrains with position feedback only

Cited by 60 publications

References 22 publications

Self-Learning Event Mistiming Detector Based on Central Pattern Generator

Self-Learning Event Mistiming Detector Based on Central Pattern Generator

Locomotion Control of Quadruped Robots With Online Center of Mass Adaptation and Payload Identification

Design of bionic goat quadruped robot mechanism and walking gait planning

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