Small-Sized Reconfigurable Quadruped Robot With Multiple Sensory Feedback for Studying Adaptive and Versatile Behaviors

Sun, Tao; Xiong, Xiaofeng; Dai, Zhendong; Manoonpong, Poramate

doi:10.3389/fnbot.2020.00014

Cited by 24 publications

(19 citation statements)

References 35 publications

(57 reference statements)

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“…The controller was proposed for easily demonstrating the PM and PR in an integrative manner. The PM and PR have numerous forms that comply with different CPG models and robots (Kimura et al, 2007;Owaki et al, 2013;Barikhan et al, 2014;Sun et al, 2020). To compare the PM and PR conveniently and consistently, four neural SO (2) oscillators are used as four decoupled CPGs.…”

Section: Adaptive Neural Controllermentioning

confidence: 99%

“…The experimental platform for studying the PM and PR is a quadruped robot in the simulation. The simulated robot is based on a small-size quadruped robot with multiple sensory feedback (Lilibot) which was developed in our previous works (Sun et al, 2020). The simulation environment was built using CoppeliaSim 2 with physical engine Vortex 3 .…”

Section: Experimental Platformmentioning

confidence: 99%

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A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion

et al. 2021

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Walking animals demonstrate impressive self-organized locomotion and adaptation to body property changes by skillfully manipulating their complicated and redundant musculoskeletal systems. Adaptive interlimb coordination plays a crucial role in this achievement. It has been identified that interlimb coordination is generated through dynamical interactions between the neural system, musculoskeletal system, and environment. Based on this principle, two classical interlimb coordination mechanisms (continuous phase modulation and phase resetting) have been proposed independently. These mechanisms use decoupled central pattern generators (CPGs) with sensory feedback, such as ground reaction forces (GRFs), to generate robot locomotion autonomously without predefining it (i.e., self-organized locomotion). A comparative study was conducted on the two mechanisms under decoupled CPG-based control implemented on a quadruped robot in simulation. Their characteristics were compared by observing their CPG phase convergence processes at different control parameter values. Additionally, the mechanisms were investigated when the robot faced various unexpected situations, such as noisy feedback, leg motor damage, and carrying a load. The comparative study reveals that the phase modulation and resetting mechanisms demonstrate satisfactory performance when they are subjected to symmetric and asymmetric GRF distributions, respectively. This work also suggests a strategy for the appropriate selection of adaptive interlimb coordination mechanisms under different conditions and for the optimal setting of their control parameter values to enhance their control performance.

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Section: Adaptive Neural Controllermentioning

confidence: 99%

Section: Experimental Platformmentioning

confidence: 99%

A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion

et al. 2021

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“…Furthermore, the robot can only deal with walking on a flat terrain. Walking on uneven or complex terrains will require additional control mechanisms, like local leg extension, elevation control (Manoonpong et al, 2013 ), and impedance control with online adaptation (Xiong and Manoonpong, 2018 ; Sun et al, 2020 ). Thus, in the future, we will further investigate the integration of posture control, local leg control, and muscle models into the control system to achieve self-organized locomotion with high adaptability for traversing on complex terrains.…”

Section: Discussionmentioning

confidence: 99%

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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“…The simplified foot structures in several-legged robots do not allow the inclusion of GRF sensors, which are useful for developing adaptive locomotion control strategies. One example is the Lilibot robot, which is a small-sized robot developed for research and education purposes (Sun et al, 2020 ). The first attempt to solve the GRF acquisition problem adopted a simple parametric model utilizing the current through the servo motors at the knee joints as the input signal; the current was found to be positively correlated with the GRF.…”

Section: Methodsmentioning

confidence: 99%

“…The linear relationship between the joint torques and motor currents ensures that the proposed model can be applied in the robot to easily acquire information on the currents absorbed by each motor. Moreover, a significant improvement over the model in Sun et al ( 2020 ) is the development of a unique network that utilizes the information coming from all four legs to estimate the GRF signals. This approach allows local faults within the joint sensory acquisition system to be handled and provides a good reconstruction of the GRF associated with a leg even if the corresponding joint signals are not available.…”

Section: Methodsmentioning

confidence: 99%

Echo State Networks for Estimating Exteroceptive Conditions From Proprioceptive States in Quadruped Robots

et al. 2021

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We propose a methodology based on reservoir computing for mapping local proprioceptive information acquired at the level of the leg joints of a simulated quadruped robot into exteroceptive and global information, including both the ground reaction forces at the level of the different legs and information about the type of terrain traversed by the robot. Both dynamic estimation and terrain classification can be achieved concurrently with the same reservoir computing structure, which serves as a soft sensor device. Simulation results are presented together with preliminary experiments on a real quadruped robot. They demonstrate the suitability of the proposed approach for various terrains and sensory system fault conditions. The strategy, which belongs to the class of data-driven models, is independent of the robotic mechanical design and can easily be generalized to different robotic structures.

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Small-Sized Reconfigurable Quadruped Robot With Multiple Sensory Feedback for Studying Adaptive and Versatile Behaviors

Cited by 24 publications

References 35 publications

A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion

A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion

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

Echo State Networks for Estimating Exteroceptive Conditions From Proprioceptive States in Quadruped Robots

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