Compliance Control of a Legged Robot Based on Improved Adaptive Control: Method and Experiments

Guo

Liu

et al. 2017

Sensors

Self Cite

In order to find a common approach to plan the turning of a bio-inspired hexapod robot, a locomotion strategy for turning and deviation correction of a hexapod walking robot based on the biological behavior and sensory strategy of ants. A series of experiments using ants were carried out where the gait and the movement form of ants was studied. Taking the results of the ant experiments as inspiration by imitating the behavior of ants during turning, an extended turning algorithm based on arbitrary gait was proposed. Furthermore, after the observation of the radius adjustment of ants during turning, a radius correction algorithm based on the arbitrary gait of the hexapod robot was raised. The radius correction surface function was generated by fitting the correction data, which made it possible for the robot to move in an outdoor environment without the positioning system and environment model. The proposed algorithm was verified on the hexapod robot experimental platform. The turning and radius correction experiment of the robot with several gaits were carried out. The results indicated that the robot could follow the ideal radius and maintain stability, and the proposed ant-inspired turning strategy could easily make free turns with an arbitrary gait.

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Turning and Radius Deviation Correction for a Hexapod Walking Robot Based on an Ant-Inspired Sensory Strategy

Guo

Liu

et al. 2017

Sensors

Self Cite

“…It is easy to work out corrected root joint angle: By substituting them into Supplementary Materials (6) and Supplementary Materials (9) for correction, the corrected joint angles can be solved, respectively, as is shown in (17) and (18). When the legs represent the front legs of a multifooted robot, ( 17) is positive, and when the legs represent the middle hind legs of the robot, the equation is negative.…”

Section: Kinematics Correction Ofmentioning

confidence: 99%

Position-Posture Control of Multilegged Walking Robot Based on Kinematic Correction

Zhang

Zhang

et al. 2020

Journal of Robotics

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Posture-position control is the fundamental technology among multilegged robots as it is hard to get an effective control on rough terrain. These robots need to constantly adjust the position-posture of its body to move stalely and flexibly. However, the actual footholds of the robot constantly changing cause serious errors during the position-posture control process because their foot-ends are basically in nonpoint contact with the ground. Therefore, a position-posture control algorithm for multilegged robots based on kinematic correction is proposed in this paper. Position-posture adjustment is divided into two independent motion processes: robot body position adjustment and posture adjustment. First, for the two separate adjustment processes, the positions of the footholds relative to the body are obtained and their positions relative to the body get through motion synthesis. Then, according to the modified inverse kinematics solution, the joint angles of the robot are worked out. Unlike the traditional complex closed-loop position-posture control of the robot, the algorithm proposed in this paper can achieve the purpose of reducing errors in the position-posture adjustment process of the leg-foot robot through a simple and general kinematic modification. Finally, this method is applied in the motion control of a bionic hexapod robot platform with a hemispherical foot-end. A comparison experiment of linear position-posture change on the flat ground shows that this method can reduce the attitude errors, especially the heading error reduced by 55.46%.

“…Each leg has three joints: base joint, hip joint, and knee joint. The robot is suitable for outdoor work due to its low energy consumption and large load characteristics [21]. The robot is controlled by a backward control based on a σ-Hopf oscillator with decoupled parameters for smooth locomotion [22].…”

Section: Hexapod Walking Robot: Smarthexmentioning

confidence: 99%

SURF-BRISK–Based Image Infilling Method for Terrain Classification of a Legged Robot

Jia

et al. 2019

Applied Sciences

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In this study, we propose adaptive locomotion for an autonomous multilegged walking robot, an image infilling method for terrain classification based on a combination of speeded up robust features, and binary robust invariant scalable keypoints (SURF-BRISK). The terrain classifier is based on the bag-of-words (BoW) model and SURF-BRISK, both of which are fast and accurate. The image infilling method is used for identifying terrain with obstacles and mixed terrain; their features are magnified to help with recognition of different complex terrains. Local image infilling is used to improve low accuracy caused by obstacles and super-pixel image infilling is employed for mixed terrain. A series of experiments including classification of terrain with obstacles and mixed terrain were conducted and the obtained results show that the proposed method can accurately identify all terrain types and achieve adaptive locomotion.