Efficient Modeling and Evaluation of Constraints in Path Planning for Multi-Legged Walking Robots

Belter, Dominik

doi:10.1109/access.2019.2933178

Cited by 15 publications

(16 citation statements)

References 48 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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“…On the other hand, high terrain mobility can be achieved even with a single DoF per leg as it is demonstrated by robots from the RHex family [9], [43]. However, the RHex robot cannot rely on precise locomotion control, as it is not capable of negotiating individual footsteps [44] or optimize its posture [36], which is essential in heavily cluttered terrains.…”

Section: Related Workmentioning

confidence: 99%

“…As one of the research streams, biologically inspired neural networks including CPGs [47], [48] are widely used for control of multi-legged robots like Alpha [34] or MORPH [37] which has been designed specifically as a modular testbed for locomotion control strategies. On the other hand, the robot motion can be governed by deliberative control strategies including blind locomotion control [23] or precise foothold planning based on exteroceptive sensing [44]. Nevertheless, the tactile sensing is required as a part of the control approach for successful foothold adaptation in challenging terrains.…”

Section: Related Workmentioning

confidence: 99%

“…Further, the adaptive terrain sensing does not require any additional sensors for the robot to overcome rough terrains. Besides, the representation of the kinematics tasks in the global reference frame greatly simplifies the formulation of the control approach, which, in turn, is easily extendable to full deliberative control that requires exteroceptive sensing [44], [60]. The performance of the presented locomotion controller in the real-world deployment of the built prototype of HAntR is reported in the next section.…”

Section: A Foot-contact Detectionmentioning

confidence: 99%

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Design, Construction, and Rough-Terrain Locomotion Control of Novel Hexapod Walking Robot With Four Degrees of Freedom Per Leg

2021

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Multi-legged walking robots are suitable platforms for unstructured and rough terrains because of their immense locomotion capabilities. These are, however, redeemed by more sophisticated control and energy-demanding motion in comparison to wheeled robots. Particularly, electrically actuated multi-legged walking robots suffer from the adverse ratio between the robot body weight and payload capacity. Moreover, the ratio of the locomotion speed and endurance is far from what can be achieved with wheeled robots. In this paper, we focus on six-legged walking robots with statically-stable gait. Based on the analysis of existing solutions, we propose a novel construction of the affordable electrically actuated robot with substantial improvements in its motion capabilities, locomotion speed, reliability, and endurance. The proposed design is implemented in a Hexapod Ant Robot (HAntR) that is accompanied by the developed locomotion control approach to improve its rough terrains negotiation capabilities by the active distribution of the robot weight to the legs in the stance phase. Properties of the robot have been experimentally verified in extensive deployments, and based on the experimental benchmarking of the built prototype, HAntR is capable of locomotion for over an hour with the payload of 85% of its weight, and its maximum crawled distance per one second is 87 % of its nominal length. HAntR represents significant improvements not only regarding the robots with identical actuators but also in comparison to other existing platforms. Therefore, we consider the robot HAntR represents a step further towards a wide range of future applications and deployments of six-legged walking robots.

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“…Zhang et al [13] introduced a complex leg force sensing system and designed a joint torque sensor to implement a force sensing system within the robot control architecture. Belter [14] proposed a new constraint evaluation method for path planning of multi-leg walking robots. Through the application of Gaussian Mixture (GM) to establish the constraint model, with the help of the proposed analytical constraint function, the robot can check the self-collision and the working space within a few microseconds, and effectively plan the robot's motion.…”

Section: Introductionmentioning

confidence: 99%

Research on the Stationarity of Hexapod Robot Posture Adjustment

Zhang

Wang

Gao

et al. 2020

Sensors

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This paper proposes a smooth adjustment method for the instability problem that occurs during the start and stop of a multi-footed robot during attitude change. First, kinematics analysis is used to establish the mapping relationship between the joint angles of the robot support legs and the body posture. The leg joint angle is a known quantity that can be measured accurately and in real time. Therefore, when the position of the foot end of the support leg is unchanged, a unique set of joint angles can be obtained with the change of body posture at a certain moment. Based on the designed mapping model, the smooth adjustment of the posture can be achieved by the smooth adjustment of the support legs. Second, a constraint index that satisfies the requirements of the robot’s steady adjustment of the robot is given. The S-curve acceleration/deceleration method is used to plan the body’s attitude angle transformation curve, and then the mapping control relationship is used to obtain the control trajectory requirements of the joint to achieve smooth adjustment. In addition, this paper also gives a simple choice and motion control method for the redundancy problem caused by the number of support legs of a multi-footed robot when the attitude is changed. The simulation and prototype experiments verify and analyze the proposed method. The results of comparative experiments show that the posture adjustment method proposed in this paper has continuous acceleration without breakpoints, the speed changes gently during the start and stop phases of the attitude transformation, and there is no sudden change in the entire process, which improves the consistency of the actual values of the attitude planning curve with the target values. The physical prototype experiment shows that the maximum deviation between the actual value of the attitude angular velocity and the target value changes from 62.5% to 5.5%, and the degree of fit increases by 57.0%. Therefore, this study solves the problem of the instability of the fuselage when the robot changes its attitude, and it provides an important reference for the multi-footed robot to improve the terrain adaptability.

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Efficient Modeling and Evaluation of Constraints in Path Planning for Multi-Legged Walking Robots

Cited by 15 publications

References 48 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

Design, Construction, and Rough-Terrain Locomotion Control of Novel Hexapod Walking Robot With Four Degrees of Freedom Per Leg

Research on the Stationarity of Hexapod Robot Posture Adjustment

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