Analysis of Creeping Locomotion of a Snake-like Robot on a Slope

The diverse locomotion modes and physiology of biological snakes make them supremely adapted for their environment. To model the noteworthy features of these snakes we have developed a snake-like robot that has no forward direction driving force. In order to enhance the ability of our robot to adapt to the environment, in this study we investigate the creeping locomotion of a snake-like robot on a slope. A computer simulator is presented for analysis of the creeping locomotion of the snake-like robot on a slope, and the environmentally-adaptable body shape for our robot is also derived through this simulator.     

Influence of the gradient of a slope on optimal locomotion curves of a snake-like robot

Snakes perform many kinds of movement adapted to different environments. Utilizing the snake as a model, we have developed a two-dimensional snake-like robot that emulates a snakes' function. To make our robot move optimally while adapting to the slope of the environment, in this study we discuss the influence of the gradient of a slope on the creeping locomotion of the robot and derive optimal creeping locomotion curves that adapted to the given slopes.     

Adaptive creeping locomotion of a CPG-controlled snake-like robot to environment change

In this paper, we present a biomimetic approach which is based on Central Pattern Generator (CPG) to solve the difficulty in control of a snake-like robot with a large number of degrees of freedom. A new network with a feedback connection is proposed, which can generate uniform outputs without any additional adjustment. The relations between the CPG parameters and the characteristics of output are also investigated. A simulation platform is also established for the analysis of the CPG-based locomotion control of a snake-like robot. To figure out adaptive creeping locomotion of the robot to the environment with changed friction or the given slope, the relations of CPG parameters and locomotion efficiency by the proposed curvature adaptive principle have been discussed.     

基于能量的蛇形机器人蜿蜒运动控制方法的仿真与实验研究

能量作为最基本的物理量之一, 联系着蛇形机器人蜿蜒运动的各个方面. 能量耗散描述了环境交互作用, 能量转换对应着运动的动力学过程, 能量平衡反映了蜿蜒运动的协调性. 提出一种基于能量的蛇形机器人蜿蜒运动控制方法-被动蜿蜒. 通过输出关节力矩控制机器人蜿蜒运动, 由机器人的能量状态调整力矩的大小. 仿真结果显示了被动蜿蜒控制下机器人的构形、角度、力矩、能量状态和转弯特性, 并对控制力矩进行了递归分析. 基于Optotrak运动测量系统构建了被动蜿蜒控制的模拟/物理混合实验系统. 进行了移动实验和拖动实验, 前者改变环境的摩擦特性,后者改变机器人的负载. 仿真和实验验证了蛇形机器人被动蜿蜒控制的有效性和适应性.     

A unified dynamic model for locomotion and manipulation of a snake-like robot based on differential geometry

A snake-like robot, whose body is a seried-wound articulated mechanism, can move in various environments. In addition, when one end is fixed on a base, the robot can manipulate objects. A method of dynamic modeling for locomotion and manipulation of the snake-like robot is developed in order to unify the dynamic equations of two states. The transformation from locomotion to manipulation is a mechanism reconfiguration, that is, the robot in locomotion has not a fixed base, but it in manipulation ha...     

Genetic programming incorporating biased mutation for evolution and adaptation of Snakebot

In this work we propose an approach for incorporating learning probabilistic context-sensitive grammar (LPCSG) in genetic programming (GP), employed for evolution and adaptation of locomotion gaits of a simulated snake-like robot (Snakebot). Our approach is derived from the original context-free grammar which usually expresses the syntax of genetic programs in canonical GP. Empirically obtained results verify that employing LPCSG contributes to the improvement of computational effort of both (i) the evolution of the fastest possible locomotion gaits for various fitness conditions and (ii) adaptation of these locomotion gaits to challenging environment and degraded mechanical abilities of the Snakebot.     

基于微分几何的蛇形机器人移动与操作统一动力学模型研究

蛇形机器人本体是一种多关节串联机构,可以在各种环境中运动,并且当一端固定时可以实现操作.本文提出一种蛇形机器人移动与操作的统一动力学建模方法,统一蛇形机器人移动状态及操作状态的动力学方程.机器人从移动状态到操作状态的转换意味着机构上的重构,即移动状态无固定基座,而操作状态有固定基座.应用虚设机构法在机构学上统一这两种状态(即构形空间中的嵌入关系),利用指数积公式描述这两种状态的运动学方程.在Riemann流形上建立起蛇形机器人移动和操作的动力学模型,并在对动力学模型中各项计算分析的基础上发现机器人操作动力学方程可直接由移动动力学方程退化得到,同时应用子流形的Gauss公式给出证明.由此在微分几何框架下建立蛇形机器人移动与操作的统一动力学模型.按照几何的观点将蛇形机器人移动与操作动力学模型的统一看作是子流形问题,并赋予几何意义.较单独针对蛇形机器人的一种状态(移动或操作)的动力学模型而言,这种统一的动力学模型能够更深刻地揭示蛇形机器人动力学的特征.     

基于循环抑制CPG 模型控制的蛇形机器人三维运动

具有三维运动能力和独特的节律运动方式，使生物蛇能在复杂的地形环境中生存. 大多数动物节律运动是由中央模式发生器(Central pattern generator, CPG) 控制的. 以此为理论依据, 首次以循环抑制建模机理构建蛇形机器人组合关节运动控制的CPG 模型. 证明该模型是节律输出型CPG 中微分方程维数最少的. 采用单向激励方式连接该类CPG 构建蛇形机器人三维运动神经网络控制体系，给出该CPG 网络产生振荡输出的必要条件. 应用蛇形机器人动力学模型仿真得到控制三维运动的CPG 神经网络参数，利用该CPG 网络的输出使\勘查者"成功实现三维运动. 该结果为建立未探明的生物蛇神经网络模型提供了一种全新的方法.     

Gaits-transferable CPG controller for a snake-like robot

With slim and legless body, particular ball articulation, and rhythmic locomotion, a nature snake adapted itself to many terrains under the control of a neuron system. Based on analyzing the locomotion mechanism, the main functional features of the motor system in snakes are specified in detail. Furthermore, a bidirectional cyclic inhibitory （BCl） CPG model is applied for the first time to imitate the pattern generation for the locomotion control of the snake-like robot, and its characteristics are discussed, particularly for the generation of three kinds of rhythmic locomotion. Moreover, we introduce the neuron network organized by the BCI-CPGs connected in line with unilateral excitation to switch automatically locomotion pattern of a snake-like robot under different commands from the higher level control neuron and present a necessary condition for the CPG neuron network to sustain a rhythmic output. The validity for the generation of different kinds of rhythmic locomotion modes by the CPG network are verified by the dynamic simulations and experiments. This research provided a new method to model the generation mechanism of the rhythmic pattern of the snake.     

基于Webots的蛇形机器人翻滚运动仿真及实现

针对蛇形机器人的侧向翻滚运动,给出一种建立正交关节蛇形机器人三维空间运动模型的方法,提出了一种更为简单的实现蛇形机器人侧向翻滚运动的舵机输入函数.通过选择不同的控制参数,可以实现蛇形机器人"U"字形和"V"字形侧向翻滚运动.在Webots移动机器人仿真软件上进行正交关节蛇形机器人翻滚运动仿真,并在蛇形机器人本体上进行试验,验证了所提控制规律的有效性.     

Reinforcement learning in dynamic environment: abstraction of state-action space utilizing properties of the robot body and environment

In this paper, we address the autonomous control of a 3D snake-like robot through the use of reinforcement learning, and we apply it in a dynamic environment. In general, snake-like robots have high mobility that is realized by many degrees of freedom, and they can move over dynamically shifting environments such as rubble. However, this freedom and flexibility leads to a state explosion problem, and the complexity of the dynamic environment leads to incomplete learning by the robot. To solve these problems, we focus on the properties of the actual operating environment and the dynamics of a mechanical body. We design the body of the robot so that it can abstract small, but necessary state-action space by utilizing these properties, and we make it possible to apply reinforcement learning. To demonstrate the effectiveness of the proposed snake-like robot, we conduct experiments; from the experimental results we conclude that learning is completed within a reasonable time, and that effective behaviors for the robot to adapt itself to an unknown 3D dynamic environment were realized.     

新型蛇形机器人蜿蜒运动的动力学分析

为提高蛇形机器人执行各种运动的能力,研制了新型蛇形机器人系统．重点研究了该蛇形机器人的动力学．建立了机器人的运动学模型,并根据运动学模型提出了控制蛇形机器人蜿蜒运动的复合运动控制方法．用拉格朗日方法建立动力学模型,对不同参数下蛇形机器人的关节力矩特性和摩擦力特性进行了分析比较,为蛇形机器人的有效运动提供了理论依据．     

Adaptive controller design for underwater snake robot with unmatched uncertainties

Because of hydrodynamic model error of the present dynamic model, there is a challenge in controller design for the underwater snake-like robot. To tackle this challenge, this paper proposes an adaptive control schemes based on dynamic model for a planar, underwater snake-like robot with model error and time-varying noise. The adaptive control schemes aim to achieve the adaptive control of joint angles tracking and the direction of locomotion control. First, through approximation and reducibility using Taylor expansion method, a simplified dynamics model of a planar amphibious snake-like robot is derived. Then, the L1 adaptive controller based on piecewise constant adaptive law is applied on the simplified planar, underwater snake-like robot, which can deal with both matched and unmatched nonlinear uncertainties. Finally, to control the direction of locomotion, an auxiliary bias signal is used as the control input to regulate the locomotion direction. Simulation results show that this L1 adaptive controller is valid to deal with different uncertainties and achieve the joint angles tracking and fast adaptive at the same time. The modified L1 adaptive controller, in which the auxiliary bias item is added, has the ability to change the direction of locomotion, that is, the orientation angle is periodic with arbitrarily given constant on average.     

基于控制函数的蛇形机器人攀爬运动分析

为实现对正交关节蛇形机器人多种运动形式的简单、统一控制,从研究蛇形机器人控制函数出发,提出了一种简单的并可同时实现正交关节蛇形机器人蜿蜒运动、行波运动、侧向翻滚运动和螺旋攀爬运动等多种运动形式的控制函数.对蛇形机器人实现螺旋攀爬运动的控制参数进行了分析,并用粒子群优化算法(PSO)对控制参数进行了优化拟合,给出了控制参...     

基于路径积分强化学习方法的蛇形机器人目标导向运动

路径积分方法源于随机最优控制,是一种数值迭代方法,可求解连续非线性系统的最优控制问题,不依赖于系统模型,快速收敛.文中将基于路径积分强化学习的策略改善方法用于蛇形机器人的目标导向运动.使用路径积分强化学习方法学习蛇形机器人步态方程的参数,不仅可以在仿真环境下使蛇形机器人规避障碍到达目标点,利用仿真环境的先验知识也能在实际环境下快速完成相同的任务.实验结果验证方法的正确性.     

A Simplified CPGs Network with Phase Oscillator Model for Locomotion Control of a Snake-like Robot

CPG (Central pattern generator) is a dynamical system of coupled nonlinear oscillators or neural networks inspired by a control mechanism in animal bodies. Without any rhythmic inputs, the CPG has the ability to produce oscillatory patterns. This paper presents a novel structure of a CPG network which can produce rhythmic motion that imitates movement of animals such as snake and lamprey. The focus is on the locomotion control of a snake-like robot, where phase oscillator has been adopted as the dynamical model to control the harmonic motion of the CPG network. There are two main points addressed in this paper: (1) simple network structure of unidirectional coupling oscillators, and (2) a single parameter to control the body shape and to control the forward and backward movement of the snake-like robot. The proposed CPG network is designed to have a simple structure with less complexity, less mathematical computation, fast convergence speed and exhibit limit cycle behavior. In addition, a new parameter, τ is introduced to control the smoothness of the CPG output as well as the speed of the snake-like robot. Simulation and experimental results show that the proposed CPG network can be used to control the serpentine locomotion of a snake-like robot.     

A lattice-type reconfigurable robotic system for achieving gaits of chain-type robots

Traditional lattice-type reconfigurable robots can only achieve the flow-style locomotion with low efficiency. Since gaits of chain-type robots are proved to be efficient and practical, this paper presents a novel lattice distortion approach for lattice-type reconfigurable robots to achieve locomotion gaits of chain-type robots. Using this approach, the robotic system can be actuated by local lattice distortion to move as an ensemble. In this paper, a rule that makes the lattice distortion equivalent to joint rotation is presented firstly. Then, a kind of module structure is designed according to requirements of the lattice distortion. Finally, a motion planning for achieving locomotion is developed, which works well in physics-based simulations of completing a serpentine locomotion gait of a snake-like robot and a tripod gait of a hexapod robot.     

Locomotion of snake-like robots using adaptive neural oscillators

This paper proposes a CPG-based control architecture using a frequency-adaptive oscillator for undulatory locomotion of snake-like robots. The control architecture consists of a network of neural oscillators that generates desired oscillatory output signals with specific phase lags. A key feature of the proposed architecture is a self-adaptation process that modulates the parameters of the CPG to adapt the motion of the robot to varying coefficients of body-ground friction. This process is based on the frequency-adaptation rule of the oscillator that is designed to learn the periodicity of sensory feedback signals. It has an important meaning of establishing a closed-loop CPG much more robust against environmental and/or system parameter changes. We verify the validity of the proposed locomotion control system employing a simulated snake-like robot moving over terrains with different friction coefficients with a constant velocity.     

NSGA-Ⅱ在蛇形机器人中的优化与控制

研究蛇形机器人蜿蜒运动步态的优化与控制问题。结合摩擦力模型,并分析蛇形机器人运动步态模型,根据基于闭环反馈的控制系统结构运用PID控制器对其步态进行跟踪控制,在此基础上采用基于非支配排序遗传算法(NSGA-Ⅱ)对步态进行优化,该优化方法实现对闭环反馈跟踪控制系统的参数优化。仿真结果表明,NSGA-Ⅱ算法能达到变量优化目的,在功率和速度之间寻找最优值,对于解决蛇形机器人运动步态多目标优化问题是可行有效的。