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Target tracking control of a bionic mantis shrimp robot with closed-loop central pattern generators

OCEAN ENGINEERING 2024年 297卷

作者： Chen, Gang Xu, Yidong Yang, Xin Hu, Huosheng Cheng, Hao Zhu, Lvyuan Zhang, Jingjing Shi, Jianwei Chai, Xinxue Zhejiang Sci Tech Univ Sch Mech Engn Hangzhou 310018 Peoples R China Univ Essex Sch Comp Sci & Elect Engn Colchester CO4 3SQ England Zhejiang Inst Ind & Informat Technol Hangzhou 310000 Peoples R China Zhejiang Machinery Ind Federat Hangzhou 310009 Peoples R China Zhejiang CathayBot Technol Co Ltd Jinhua 321035 Peoples R China

To address the challenge of efficient underwater target tracking, this study focuses on the mantis shrimp as a biomimetic model. The research involves the design of a bionic mantis shrimp robot featuring a structure that supports multi-pleopod coupled movement. We propose a target tracking control system based on a bionic closed-loop central pattern generator (CPG). This system integrates CPG control, proportional integral derivative control, and fuzzy logic control. It aims to enable precise target tracking by dynamically adjusting the robot's motion in response to data from vision sensors. Extensive underwater experiments validate the effectiveness of this control system in both static and dynamic target tracking scenarios. The experiments demonstrate that the bionic mantis shrimp robot can perform multiangle turns and adjust its velocity flexibly in a confined space measuring 2 m x 1 m x 1 m. Notably, the robot can track targets at angles up to 130 degrees relative to its initial motion direction. The minimum tracking turning radius achieved is 0.65 m, highlighting the potential for advanced target tracking and broader applications in underwater robotics.

关键词： central pattern generators Closed-loop CPG Target tracking control Bionic mantis shrimp robot Fuzzy logic control Underwater robot

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Fuzzy Control with central pattern generators for the Locomotion of Quadruped Robotic Systems 4th

Fuzzy Control with Central Pattern Generators for the Locomo...

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4th Latin American Workshop on Computational Neuroscience (LAWCN)

作者： Rico-Mesa, Edgar-Mario Hernandez-Riveros, Jesus-Antonio Ctr Tecnol Manufactura Avanzada Dept Elect Ind St 10469-120 Medellin 050042 Antioquia Colombia Univ Nacl Colombia Fac Minas Dept Energia Elect & Automat Career 8065-223 Medellin 050036 Antioquia Colombia

ISBN: (纸本)9783031638473;9783031638480

The development with CPG of the locomotion of a quadruped robot with three degrees of freedom per leg and its management by fuzzy control is presented. The robot, simulated in Gazebo-ROS, has three proximity sensors, an IMU sensor, and an odometry sensor. The purpose of the robot is the execution of locomotion in different types of movement. To reproduce the motor function of locomotion the central pattern generators use a novel mathematical model. The robot's environment is a labyrinth on a flat surface. A three-level control architecture operates the robot's locomotion. At levels I and II, the motor function of locomotion is reproduced with central pattern generators. Level III plans locomotion movement. This level has parallel control of both obstacle avoidance with a fuzzy controller and robot stability with a central pattern generator. The priority in motion planning is the stability of the robot. The proper functioning of the robot control architecture is demonstrated.

关键词： central pattern generators Stability Reflex Movements Fuzzy Control Quadruped Robot Gazebo ROS

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Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

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JOURNAL OF NEURAL ENGINEERING 2023年第6期20卷 066006-066006页

作者： Di Russo, Andrea Stanev, Dimitar Sabnis, Anushree Danner, Simon M. Ausborn, Jessica Armand, Stephane Ijspeert, Auke Ecole Polytech Fed Lausanne BioRobot Lab Lausanne Switzerland Drexel Univ Coll Med Dept Neurobiol & Anat Philadelphia PA USA Univ Geneva Geneva Univ Hosp Kinesiol Lab Geneva Switzerland

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms, which activate and deactivate reflexes depending on the detected gait cycle phases. However, the physiological interpretation of these state machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion. Approach. We propose a bio-inspired controller composed of two coupled CPGs that produce the rhythm and pattern, and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The musculoskeletal model is composed of a skeletal structure and nine muscles per leg generating movement in sagittal plane. Main results. Optimizing the open parameters for effort minimization and stability, human kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, periodic motion could not be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce ranges of speeds from 0.3 to 1.9 m s-1. The results showed that the net influence of feedback on motoneurons (MNs) during perturbed locomotion is predominantly inhibitory and that the CPGs provide the timing of MNs' activation by exciting or inhibiting muscles in specific gait phases. Significance. The proposed bio-inspired controller could

关键词： human locomotion simulations sensory feedback central pattern generators gait modulation

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Design Principles for central pattern generators With Preset Rhythms

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2020年第9期31卷 3658-3669页

作者： Lodi, Matteo Shilnikov, Andrey L. Storace, Marco Univ Genoa Dept Elect Elect Telecommun Engn & Naval Architec I-16145 Genoa Italy Georgia State Univ Neurosci Inst Dept Math & Stat Atlanta GA 30303 USA

This article is concerned with the design of synthetic central pattern generators (CPGs). Biological CPGs are neural circuits that determine a variety of rhythmic activities, including locomotion, in animals. A synthetic CPG is a network of dynamical elements (here called cells) properly coupled by various synapses to emulate rhythms produced by a biological CPG. We focus on CPGs for locomotion of quadrupeds and present our design approach, based on the principles of nonlinear dynamics, bifurcation theory, and parameter optimization. This approach lets us design the synthetic CPG with a set of desired rhythms and switch between them as the parameter representing the control actions from the brain is varied. The developed four-cell CPG can produce four distinct gaits: walk, trot, gallop, and bound, similar to the mouse locomotion. The robustness and adaptability of the network design principles are verified using different cell and synapse models.

关键词： Mice Synapses Legged locomotion Biological system modeling Mathematical model Cells (biology) Bifurcation analysis central pattern generators neuronal models parameter optimization

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Dynamical State Forcing on central pattern generators for Efficient Robot Locomotion Control 27th

Dynamical State Forcing on Central Pattern Generators for Ef...

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27th International Conference on Neural Information Processing

作者： Chuthong, Thirawat Leung, Binggwong Tiraborisute, Kawee Ngainkajorriwiwat, Potiwat Manoonpong, Poramate Dilokthanakul, Nat Vidyasirimedhi Inst Sci & Technol Sch Informat Sci & Technol Bioinspired Robot & Neural Engn Lab Rayong 21210 Thailand Univ Southern Denmark Maersk Mc Kinney Moller Inst Embodied AI & Neurorobot Lab Odense Denmark Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Inst Bioinspired Struct & Surface Engn Nanjing Peoples R China

ISBN: (纸本)9783030638320;9783030638337

Many CPG-based locomotion models have a problem known as the tracking error problem, where the mismatch between the CPG driving signal and the state of the robot can cause undesirable behaviours for legged robots. Towards alleviating this problem, we introduce a mechanism that modulates the CPG signal using the robot's interoceptive information. The key concept is to generate a driving signal that is easier for the robot to follow, yet can drive the locomotion of the robot. This can be done by nudging the CPG signal in the direction of lower tracking error, which can be analytically calculated. Unlike other reactive CPG, the proposed method does not rely on any parametric learning ability to adjust the shape of the signal, making it a unique option for a biological adaptive motor control. Our experiment results show that the proposed method successfully reduces the tracking error. We also show that the CPG signal, regulated by the proposed method, is robust to perturbation and can smoothly return back to the default pattern.

关键词： central pattern generators Locomotion control PID controller

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A controller perspective on biological gait control: Reflexes and central pattern generators

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ANNUAL REVIEWS IN CONTROL 2019年 48卷 392-400页

作者： Duysens, Jacques Forner-Cordero, Arturo Univ Sao Paulo Escola Politecn Mechatron Dept Biomechatron Lab Av Prof Mello Moraes 2231 BR-05508030 Sao Paulo SP Brazil Katholieke Univ Leuven FaBeR Dept Kinesiol Leuven Belgium

Biological motion control paradigms can be analyzed from a control theory point of view and translated to control applications. This paper revises and updates important aspects about the neural control of biped gait based on the central pattern Generator (CPG) and provides a controller view, including possible artificial implementations of these controllers. A first aspect to consider is the biological sensor-actuation system because the particularities of this system: the mammalian muscle. Many current biped robots are based on symmetrical CPG. However, new evidence suggests that biological CPG is asymmetrical with rhythm generator controlling the flexor half in a kind of feedforward control and the extensor behaving in a feedback fashion controlled by external inputs such as ground contact. A theoretical model of the CPG connections with flexors and extensors is presented. (C) 2019 Published by Elsevier Ltd.

关键词： Locomotion control central pattern generators reflexes neural control

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Design of Synthetic central pattern generators Producing Desired Quadruped Gaits

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2018年第3期65卷 1028-1039页

作者： Lodi, Matteo Shilnikov, Andrey Storace, Marco Univ Genoa Dept Elect Elect Telecommun Engn & Naval Architec I-16145 Genoa Italy Georgia State Univ Neurosci Inst Atlanta GA 30303 USA

This paper is concerned with a method for design and analysis of specific neuronal networks, called central pattern generators (CPGs), which produce primary rhythmic patterns in animals. In particular, the paper is focused on synthetic CPGs made up of few basic elements and governing quadrupeds' gaits and gait transitions, under the control of an external drive. The method combines the principles of bifurcation theory, geometric properties of symmetry, and numerical analysis based on the recently proposed toolbox CEPAGE. The method is applied to two CPGs, one bio-inspired and one purely synthetic. In both the cases, the method provides a way to obtain a desired sequence of gaits by continuously changing a bifurcation parameter related to the external drive.

关键词： central pattern generators dynamical systems bifurcation analysis

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Locomotion Control of Quadruped Robot Based on central pattern generators 30

Locomotion Control of Quadruped Robot Based on Central Patte...

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30th Chinese Control and Decision Conference (CCDC)

作者： Liu, Houde Wang, Xiang Wang, Xueqian Liang, Bin Tsinghua Univ Grad Sch Shenzhen Shenzhen 518005 Peoples R China Tsinghua Univ Natl Lab Informat Sci & Technol Beijing 100030 Peoples R China Tsinghua Univ Shenzhen Res Inst Shenzhen 518057 Peoples R China

ISBN: (纸本)9781538612446

The central pattern generators (CPGs) have gained the favor of many researchers due to their stable limit circle properties in recent years. However, simple CPGs can merely implement open-loop control, which means attitude of robot body cannot he controlled effectively. In this paper, we present a controller for quadruped robot locomotion in the flat and slope. The attitude reflex is implemented as sensory feedback augmenting the CPGs. The control strategy is verified on a 3D quadruped robot plat-form in SimMechanics. And finally we realize the stable straight-line walking for the quadruped robot in the flat terrain and the slope.

关键词： central pattern generators Quadruped Robot Straight-line Walking

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Locomotion Control of Quadruped Robot Based on central pattern generators

Locomotion Control of Quadruped Robot Based on Central Patte...

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第30届中国控制与决策会议

作者： Houde Liu Xiang Wang Xueqian Wang Bin Liang Tsinghua University Graduate School at Shenzhen Tsinghua University National Laboratory for Information Science and Technology Research Institute of Tsinghua University in Shenzhen

The central pattern generators(CPGs) have gained the favor of many researchers due to their stable limit circle properties in recent years. However, simple CPGs can merely implement open-loop control, which means attitude of robot body cannot be controlled effectively. In this paper, we present a controller for quadruped robot locomotion in the flat and slope. The attitude reflex is implemented as sensory feedback augmenting the CPGs. The control strategy is verified on a 3 D quadruped robot platform in SimMechanics. And finally we realize the stable straight-line walking for the quadruped robot in the flat terrain and the slope.

关键词： central pattern generators Quadruped Robot Straight-line Walking

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The influence of walking-aids on the plasticity of spinal interneuronal networks, central-pattern-generators and the recovery of gait post-stroke. A literature review and scholarly discussion

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JOURNAL OF BODYWORK AND MOVEMENT THERAPIES 2017年第2期21卷 422-434页

作者： Maguire, Clare C. Sieben, Judith M. de Bie, Robert A. Bildungszentrum Gesundheit Basel Stadt Dept Physiotherapy CH-4142 Muenchenstein Switzerland Maastricht Univ CAPHRI Sch Publ Hlth & Primary Care NL-6200 MD Maastricht Netherlands Maastricht Univ Dept Anat & Embryol NL-6200 MD Maastricht Netherlands Maastricht Univ Dept Epidemiol NL-6200 MD Maastricht Netherlands

Background: Many aspects of post-stroke gait-rehabilitation are based on low-level evidence or expert opinion. Neuroscientific principles are often not considered when evaluating the impact of interventions. The use of walking-aids including canes and rollators, although widely used for long periods, has primarily been investigated to assess the immediate kinetic, kinematic or physiological effects. The long-term impact on neural structures und functions remains unclear. Methods: A literature review of the function of and factors affecting plasticity of spinal interneuronal-networks and central-pattern-generators (CPG) in healthy and post-stroke patients. The relevance of these mechanisms for gait recovery and the potential impact of walking-aids is discussed. Results: Afferent-input to spinal-networks influences motor-output and spinal and cortical plasticity. Disrupted input may adversely affect post-stroke plasticity and functional recovery. Joint and muscle unloading and decoupling from four-limb CPG control may be particularly relevant. Conclusions: Canes and rollators disrupt afferent-input and may negatively affect the recovery of gait. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Cerebrovascular stroke Walking Assistive devices central pattern generators Neuronal plasticity

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