Follow-the-Contact-Point gait control of centipede-like multi-legged robot to navigate and walk on uneven terrain

Inagaki, Shinkichi; Niwa, Tomoya; Suzuki, Tatsuya

doi:10.1109/iros.2010.5651324

Cited by 31 publications

(16 citation statements)

References 11 publications

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“…On the other hand, contacting the ground with many legs is useful for avoiding stumbling in various environments. Inagaki et al ( 2010 ) proposed a distributed control method in which the legs follow the contact points of anterior legs, which allowed a robot to walk in various environments as long as the front legs choose solid footholds. Hayakawa et al ( 2020 ) proposed a gait generation strategy to ensure static stability for single-legged modular robots to create a cluster with various leg configurations.…”

Section: Discussionmentioning

confidence: 99%

Generation of Direct-, Retrograde-, and Source-Wave Gaits in Multi-Legged Locomotion in a Decentralized Manner via Embodied Sensorimotor Interaction

Ambe

Aoi

Tsuchiya

et al. 2021

Front. Neural Circuits

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Multi-legged animals show several types of ipsilateral interlimb coordination. Millipedes use a direct-wave gait, in which the swing leg movements propagate from posterior to anterior. In contrast, centipedes use a retrograde-wave gait, in which the swing leg movements propagate from anterior to posterior. Interestingly, when millipedes walk in a specific way, both direct and retrograde waves of the swing leg movements appear with the waves' source, which we call the source-wave gait. However, the gait generation mechanism is still unclear because of the complex nature of the interaction between neural control and dynamic body systems. The present study used a simple model to understand the mechanism better, primarily how local sensory feedback affects multi-legged locomotion. The model comprises a multi-legged body and its locomotion control system using biologically inspired oscillators with local sensory feedback, phase resetting. Each oscillator controls each leg independently. Our simulation produced the above three types of animal gaits. These gaits are not predesigned but emerge through the interaction between the neural control and dynamic body systems through sensory feedback (embodied sensorimotor interaction) in a decentralized manner. The analytical description of these gaits' solution and stability clarifies the embodied sensorimotor interaction's functional roles in the interlimb coordination.

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Section: Discussionmentioning

confidence: 99%

Generation of Direct-, Retrograde-, and Source-Wave Gaits in Multi-Legged Locomotion in a Decentralized Manner via Embodied Sensorimotor Interaction

Ambe

Aoi

Tsuchiya

et al. 2021

Front. Neural Circuits

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“…From the research of legged robots from the last decade, the gait pattern of a quadruped robot includes walk [ 59 ], trot [ 60 ], pace [ 61 ], gallop [ 62 ], and bound [ 63 ], which are used for different conditions and are limited by the DOF (Degree of Freedom) of the leg and actuation of each joint. The first three types of gait are used for the slow movement of robots.…”

Section: Discussionmentioning

confidence: 99%

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

Zhu

Guo

Liu

et al. 2017

Sensors

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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.

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“…This approach combines bio-inspired key ingredients including: (1) distributed neural CPG-based control circuits without inter-circuit connections for flexible and independent individual leg control, (2) a learning mechanism for proprioceptive sensory adaptation, and (3) body-environment interaction, to acquire adaptive and flexible interlimb coordination for walking robots. This novel approach has more advantages compared to others (Ijspeert et al, 2007 ; Manoonpong et al, 2008 , 2013 ; Inagaki et al, 2010 ; Asif, 2012 ; Ambe et al, 2013 ) in the following aspects:…”

Section: Introductionmentioning

confidence: 90%

“…We validated our proposed adaptive interlimb coordination approach on simulated 4-, 6-, 8-, and 20-legged robots. We believe that the study pursued here will also sharpen our understanding of how continuous online sensory adaptation with flexible plasticity can be realized and combined with control mechanisms for self-organized locomotion and fast adaptation to damage in walking systems which could not be realized solely by conventional bio-inspired control methods (Espenschied et al, 1996 ; Ijspeert et al, 2007 ; Manoonpong et al, 2008 , 2013 ; Inagaki et al, 2010 ; Asif, 2012 ; Ambe et al, 2013 ; Bjelonic et al, 2016 ) or machine learning techniques (Bongard et al, 2006 ; Cully et al, 2015 ; Hwangbo et al, 2019 ), or their combination (like CPG-based control with reinforcement learning, Ishige et al, 2019 ) (see section 5 for more details).…”

Section: Introductionmentioning

confidence: 98%

General Distributed Neural Control and Sensory Adaptation for Self-Organized Locomotion and Fast Adaptation to Damage of Walking Robots

Miguel-Blanco

Manoonpong

2020

Front. Neural Circuits

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Walking animals such as invertebrates can effectively perform self-organized and robust locomotion. They can also quickly adapt their gait to deal with injury or damage. Such a complex achievement is mainly performed via coordination between the legs, commonly known as interlimb coordination. Several components underlying the interlimb coordination process (like distributed neural control circuits, local sensory feedback, and body-environment interactions during movement) have been recently identified and applied to the control systems of walking robots. However, while the sensory pathways of biological systems are plastic and can be continuously readjusted (referred to as sensory adaptation), those implemented on robots are typically static. They first need to be manually adjusted or optimized offline to obtain stable locomotion. In this study, we introduce a fast learning mechanism for online sensory adaptation. It can continuously adjust the strength of sensory pathways, thereby introducing flexible plasticity into the connections between sensory feedback and neural control circuits. We combine the sensory adaptation mechanism with distributed neural control circuits to acquire the adaptive and robust interlimb coordination of walking robots. This novel approach is also general and flexible. It can automatically adapt to different walking robots and allow them to perform stable self-organized locomotion as well as quickly deal with damage within a few walking steps. The adaptation of plasticity after damage or injury is considered here as lesion-induced plasticity. We validated our adaptive interlimb coordination approach with continuous online sensory adaptation on simulated 4-, 6-, 8-, and 20-legged robots. This study not only proposes an adaptive neural control system for artificial walking systems but also offers a possibility of invertebrate nervous systems with flexible plasticity for locomotion and adaptation to injury.

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Follow-the-Contact-Point gait control of centipede-like multi-legged robot to navigate and walk on uneven terrain

Cited by 31 publications

References 11 publications

Generation of Direct-, Retrograde-, and Source-Wave Gaits in Multi-Legged Locomotion in a Decentralized Manner via Embodied Sensorimotor Interaction

Generation of Direct-, Retrograde-, and Source-Wave Gaits in Multi-Legged Locomotion in a Decentralized Manner via Embodied Sensorimotor Interaction

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

General Distributed Neural Control and Sensory Adaptation for Self-Organized Locomotion and Fast Adaptation to Damage of Walking Robots

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