Circling turning locomotion of a new multiple closed-chain-legs robot with hybrid-driven mechanism

A multi-legged robot based on a hybrid-driven mechanism is presented in this paper as an improvement of the legged robot based on crank-driven linkage mechanism. A hybrid-driven mechanism containing a full-rotational degree of freedom (DOF) and a linear translational DOF was obtained after a series of foot trajectory analyses on the Jansen mechanism. The stance phase trajectory of this hybrid-driven mechanism can maintain horizontality regardless of the length adjustment of the linear DOF. A turning gait of a hexapod robot based on this hybrid-driven mechanism was proposed, such that all of the legs had an identical crank angular speed, and the robot turned its orientation through different linear servo controls on the legs of the two sides. Simulation and experimental results showed that the hexapod robot could realize the turning gait when the legs of the two sides applied different length adjustments. The body center trajectories in all cases were approximate to a circle, and the smallest turning radius was close to the length of the robot. Moreover, the magnitude of the pitch and roll angles, and body center fluctuation in the simulations was all small, indicating that the hexapod robot based on the hybrid-driven mechanism was stable during the turning locomotion.     

Legged robot locomotion and gymnastics

The learning and control space of real-world autonomous agents are often many-dimensional, growing, and unbounded in nature. Such agents exhibit adaptive, incremental, exploratory, and sometimes explosive learning behaviors. Learning in adaptive neurofuzzy control, however, is often referred to as global training with a large set of random examples and a very low learning rate. This type of controller is not reorganizable; it cannot explain exploratory learning behaviors as exhibited by human and animal species. A theory of coordinated computational intelligence (CCI) is proposed in this paper which leads to a reorganizable multiagent cerebellar architecture for intelligent control. The architecture is based on the hypotheses that (1) a cerebellar system consists of a school of relatively simple and cognitively identifiable semiautonomous neurofuzzy agents; (2) autonomous control is the result of cerebellar agent fine-tuning and coordination rather than complicate computation; and (3) learning is accomplished via individual cerebellar agent learning and coordinated discovery in a learning-tuning-brainstorming process. Agent oriented decomposition and coordination algorithms are introduced; necessary and sufficient conditions are established for cerebellar agent discovery and common sense cerebellar motion law discovery. Nesting, safety, layering, and autonomy-four principles are analytically formulated for the reorganization of neurofuzzy agents.     

Undulatory locomotion and effective propulsion for fish-inspired robot

Swimming, turning, and whip-sweeping propulsion for carangiform locomotion of a fish robot are investigated by means of a 4-link planar tail and an autonomous underwater vehicle (AUV)-like model. It is observed that excellent acceleration occurs when a whip sweeping behavior has been applied to the fish tail. The forward speed can even increases twice to the nominal swimming via the simulation study. The efficient movement is thus incorporated to the fish robot for agile movement. The robot's swimming patterns realize the effect in terms of the forward swimming, turning swimming, acceleration increasing, descended swimming, ascended swimming, depth regulating, and self-stabilization. Verification is accomplished by incorporating the 4-link planar tail, AUV-like model, and a two degree-of-freedom (DOF) barycenter mechanism. The four-link planar tail and 2-DOF barycenter mechanism act, respectively, as the thrust generator and stabilizing actuator for the fish robot. Sliding mode control (SMC) has been applied for three-dimensional (3D) trajectory tracking. Simulation results illustrate satisfactory performances of the fish robot in terms of the fish-like behaviors and maneuverability, which are due to the consequence of the mimicked predator-fish behaviors and performance robustness of the SMC for trajectory tracking under ocean current perturbations and modeling uncertainties.     

Fault-tolerant locomotion of the hexapod robot

In this paper, we propose a scheme for fault detection and tolerance of the hexapod robot locomotion on even terrain. The fault stability margin is defined to represent potential stability which a gait can have in case a sudden fault event occurs to one leg. Based on this, the fault-tolerant quadruped periodic gaits of the hexapod walking over perfectly even terrain are derived. It is demonstrated that the derived quadruped gait is the optimal one the hexapod can have maintaining fault stability margin nonnegative and a geometric condition should be satisfied for the optimal locomotion. By this scheme, when one leg is in failure, the hexapod robot has the modified tripod gait to continue the optimal locomotion.     

A modular robot that exhibits amoebic locomotion

This paper discusses a fully decentralized algorithm able to control the morphology of a two-dimensional modular robot called “Slimebot”, consisting of many identical modules, according to the environment encountered. One of the significant features of our approach is that we explicitly exploit “emergent phenomena” stemming from the interplay between control and mechanical systems in order to control the morphology in real time. To this end, we particularly focus on a “functional material” and a “mutual entrainment”, the former of which is used as a spontaneous connectivity control mechanism between the modules, and the latter of which plays as the core of the control mechanism for the generation of locomotion. Simulation results indicate that the proposed algorithm can induce “amoebic locomotion”, which allows us to successfully control the morphology of the modular robot in real time according to the situation without losing the coherence of the entire system. The results obtained are expected to shed light on how control and mechanical systems should be coupled, and what the carefully designed interaction between control and mechanical systems brings to the resulting behavior.     

An approach to analyzing biped locomotion dynamics and designing robot locomotion controls

An approach to analyzing biped locomotion problems is presented. This approach applies the principles of Lagrangian dynamics to derive the equations of motion of locomotion gaits, state-variable techniques to analyze locomotion dynamics, and multivariable feedback to design locomotion controls. A robot model which has no knee joints or feet and is constrained to motion in the sagittal plane is chosen as a sufficiently simple model of a biped to illustrate the approach. A goal of the analysis is the design of a locomotion control for the robot which produces a walking gait having a velocity and stride length similar to those of a human walking gait. The principle feature of the approach is a much deeper understanding of the dynamics of biped locomotion than previous approaches have provided.     

双足机器人动态步行实时步态生成

针对双足机器人动态步行生成关节运动轨迹复杂问题,提出了一种简单直观的实时步态生成方案。建立了平面五杆双足机器人动力学模型,通过模仿人类步行主要运动特征并根据双足机器人动态步行双腿姿态变化的要求,将动态步行复杂任务分解为顺序执行的四个过程,在关节空间相对坐标系下设计了躯干运动模式、摆动腿和支撑腿动作及步行速度调整模式,结合当前步行控制结果反馈实时产生稳定的关节运动轨迹。仿真实验验证了该方法的有效性,简单易实现。     

Hierarchical control structure of a multilegged robot for environmental adaptive locomotion

We propose a biomimetic, two-layered, hierarchical control structure for adaptive locomotion of a hexapod robot. In this structure, the lower layer consists of six uniform subsystems. Each subsystem interacts locally with its neighboring subsystems, and autonomously controls its own leg movements according to the weighted sum of three basic vector fields that represent the three basic motion patterns of the robot body. The upper-layer controller decides the intended body movement, and sends the lower-layer controllers three variables as the weights of each basic vector field. This approach greatly reduces the communication between the two layers, and contributes to real-time adaptive locomotion. 3D dynamic simulations, as well as experiments with a real modularized hexapod robot, show the effectiveness of this hierarchical structure. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001     

胶囊机器人无线控制系统设计

介绍一种微型胶囊机器人的无线控制方法,首先分析了人体的生物电磁效应对无线传输的影响,根据其影响关系,选择无线射频芯片nRF905实现无线通信。上位机(PC机)和微控制器间通过USB口进行串行通信,再利用超低功耗微控制器MSP430f1232的SPI口与nRF905进行数据传输,最后在实验室的无线通信实验验证了这种方法的可行性。     

仿人机器人相似性运动研究进展

针对仿人机器人模仿人体运动问题, 从运动轨迹角度比较了基于运动解析方程方法与基于人体运动相似性方法的特点, 阐述了相似性运动系统基本结构, 分析了图像捕捉与处理、相似性特征处理、相似性运动约束与优化等模块功能, 阐述了相似性运动中的人体运动捕获与处理、运动关节解算、运动模型简化与重定向、关键姿势处理与相似度评价、关节空间位姿计算、动力学匹配约束等方面的研究现状, 最后提出了研究展望。     

Analysis of creeping locomotion of a snake-like robot

Snakes perform many kinds of movement adapted to the environment. Utilizing the snake (its forms and motion) as a model to develop a snake-like robot, that performs the snake's function, is important for generating a new type of locomotion and expanding the possible uses of robots. In this study, we developed a simulator to simulate the creeping locomotion of the snake-like robot, in which the robot dynamics is modeled and the interaction with the environment is considered through Coulomb friction. This simulator makes it possible to analyze creeping locomotion with normaldirection slip, adding to the glide along the tangential direction. Through the developed simulator, we investigate the snake-like robot creeping locomotion which is generated only by swinging each of the joints from side to side and discuss the optimal creeping locomotion of the snake-like robot that is adapted to the environment.     

Neural network control for direct-drive robot mechanisms

The theoretical development of a trajectory-tracking neural network controller based on the theory of continuous sliding-mode controllers is shown in the paper. Derived equations of the on-line adaptive neural network controller were verified on a real industrial direct-drive 3 degrees of freedom (D.O.F.) PUMA mechanism. The new neural network continuous sliding-mode controller was successfully tested for trajectory-tracking control tasks with respect to three criteria: convergence properties of the proposed control algorithm (high-speed cyclic movement, low-speed movement, high-speed PTP movement), adaptation capability of the algorithm to sudden changes in the manipulator dynamics (load), and generalization properties of the proposed control scheme. An interesting effect of the lower position error after a transient time at sudden load changes is shown.     

A control structure for the locomotion of a legged robot ondifficult terrain

The control of a legged robot walking on difficult terrain demands the development of efficient and reliable algorithms to coordinate the movement of multiple legs according to a diversity of requirements. We present a control structure, implemented on a six-legged robot, in which the aspects of stability, mobility, ground accommodation, gait generation, and robot heading are integrated in a coherent and simple way     

Learning locomotion reflexes: A self-supervised neural system for a mobile robot

This article is concerned with an artificial neural system for a mobile robot reactive navigation in an unknown, cluttered environment. Reactive navigation is a process of immediately choosing locomotion actions in response to measured spatial situations, while no planning occurs. A task of a presented system is to provide a steering angle signal letting a robot reach a goal while avoiding collisions with obstacles. Basic reactive navigation methods are briefly characterized, special attention is paid to a neural approach to the considered problem. The authors describe the system's architecture and important details of the algorithm. The main parts of the system are: the Fuzzy ART neural self-organizing classifier, performing a perceptual space partitioning, and a neural associative memory, memorizing the system's experience and superposing influences of different behaviors. Tests show that the learning process, starting from zero, is efficient, despite some initial fluctuations of its effectiveness.     

Self-organized adaptive legged locomotion in a compliant quadruped robot

In this contribution we present experiments of an adaptive locomotion controller on a compliant quadruped robot. The adaptive controller consists of adaptive frequency oscillators in different configurations and produces dynamic gaits such as bounding and jumping. We show two main results: (1) The adaptive controller is able to track the resonant frequency of the robot which is a function of different body parameters (2) controllers based on dynamical systems as we present are able to “recognize” mechanically intrinsic modes of locomotion, adapt to them and enforce them. More specifically the main results are supported by several experiments, showing first that the adaptive controller is constantly tracking body properties and readjusting to them. Second, that important gait parameters are dependent on the geometry and movement of the robot and the controller can account for that. Third, that local control is sufficient and the adaptive controller can adapt to the different mechanical modes. And finally, that key properties of the gaits are not only depending on properties of the body but also the actual mode of movement that the body is operating in. We show that even if we specify the gait pattern on the level of the CPG the chosen gait pattern does not necessarily correspond to the CPG’s pattern. Furthermore, we present the analytical treatment of adaptive frequency oscillators in closed feedback loops, and compare the results to the data from the robot experiments.

Simulation systems for the design of robot mechanisms

Building environmental models by a vision-guided mobile robot is a key problem in robotics. This paper presents a new strategy of the vision-guided mobile robot for building models of an unknown environment by panoramic sensing. The mobile robot perceives with two types of panoramic sensing: one is for acquiring omnidirectional visual information at an observation point to find the outline structure of the local environment and the other is for acquiring visual information along a route to build local environmental models. Before exploring the environment, the robot looks around and finds the outline structure of the local environment as a reference frame for acquiring the local models. Then the robot builds the local models while moving along the directions of the outline structure (the outline structure is represented by a simple convex polygon, each side of which has a direction). We have implemented the above-mentioned robot behaviors into a mobile robot which has multiple vision agents. The multiple vision agents can simultaneously execute different vision tasks needed for panoramic sensing.     

Optimal two-degree-of-freedom fuzzy control for locomotion control of a hydraulically actuated hexapod robot

Locomotion control of legged robots is a very challenging task because very accurate foot trajectory tracking control is necessary for stable walking. An electro-hydraulically actuated walking robot has sufficient power to walk on rough terrain and carry a heavier payload. However, electro-hydraulic servo systems suffer from various shortcomings such as a high degree of nonlinearity, uncertainty due to changing hydraulic properties, delay due to oil flow and dead-zone of the proportional electromagnetic control valves. These shortcomings lead to inaccurate analytical system model, therefore, application of classical control techniques result into large tracking error. Fuzzy logic is capable of modeling mathematically complex or ill-defined systems. Therefore, fuzzy logic is becoming popular for synthesis of control systems for complex and nonlinear plants. In this investigation, a two-degree-of-freedom fuzzy controller, consisting of a one-step-ahead fuzzy prefilter in the feed-forward loop and a PI-like fuzzy controller in the feedback loop, has been proposed for foot trajectory tracking control of a hydraulically actuated hexapod robot. The fuzzy prefilter has been designed by a genetic algorithm (GA) based optimization. The prefilter overcomes the flattery delay caused by the hydraulic dead-zone of the electromagnetic proportional control valve and thus helps to achieve better tracking. The feedback fuzzy controller ensures the stability of the overall system in the face of model uncertainty associated with hydraulically actuated robotic mechanisms. Experimental results exhibit that the proposed controller manifests better foot trajectory tracking performance compared to single-degree-of-freedom (SDF) fuzzy controller or optimal classical controller like state feedback LQR controller.     

Decentralized autonomous control of a quadrupedal locomotion robot using oscillators

This article deals with the design of a control system for a quadrupedal locomotion robot. The proposed control system is composed of a leg motion controller and a gait pattern controller within a hierarchical architecture. The leg controller drives actuators at the joints of the legs using a high-gain local feedback control. It receives the command signal from the gait pattern controller. The gait pattern controller, on the other hand, involves nonlinear oscillators. These oscillators interact with each other through signals from the touch sensors located at the tips of the legs. Various gait patterns emerge through the mutual entrainment of these oscillators. As a result, the system walks stably in a wide velocity range by changing its gait patterns and limiting the increase in energy consumption of the actuators. The performance of the proposed control system is verified by numerical simulations. This work was presented in part at the Fifth International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

Dynamic turning control of a quadruped locomotion robot using oscillators

We propose a dynamic turning control system for a quadruped robot that uses non-linear oscillators. It is composed of a spontaneous locomotion controller and voluntary motion controller. We verified the mechanical capabilities of the dynamic turning motion of the proposed control system through numerical simulations and hardware experiments. Various turning speeds and orientations made the motion of the robot asymmetrical in terms of the duty ratio, stride and center of pressure. The proposed controller actively and adaptively controlled redundant degrees of freedom to cancel out dynamic asymmetry, and established stable turning motion at various locomotion speeds and turning orientations.     

多摄像机图像间的稳定切换控制

为获得连续动态的图像雅可比矩阵,分析了融合方式和传统图像直接切换方法的缺陷,提出了一种基于融合的多图像稳定切换算法,算法采用动态加权融合策略。在移动机器人位置未知和无标定多摄像机的情况下,仿真和实验结果表明:该算法比传统方法具有更高的适应能力,图像切换过程的稳定性得到了很大提高。