Design and control of an IPMC wormlike robot.

This paper presents an innovative wormlike robot controlled by cellular neural networks (CNNs) and made of an ionic polymer-metal composite (IPMC) self-actuated skeleton. The IPMC actuators, from which it is made of, are new materials that behave similarly to biological muscles. The idea that inspired the work is the possibility of using IPMCs to design autonomous moving structures. CNNs have already demonstrated their powerfulness as new structures for bio-inspired locomotion generation and control. The control scheme for the proposed IPMC moving structure is based on CNNs. The wormlike robot is totally made of IPMCs, and each actuator has to carry its own weight. All the actuators are connected together without using any other additional part, thereby constituting the robot structure itself. Worm locomotion is performed by bending the actuators sequentially from "tail" to "head," imitating the traveling wave observed in real-world undulatory locomotion. The activation signals are generated by a CNN. In the authors' opinion, the proposed strategy represents a promising solution in the field of autonomous and light structures that are capable of reconfiguring and moving in line with spatial-temporal dynamics generated by CNNs.     

Gait planning based on kinematics for a quadruped gecko model with redundancy

Recent research on mobile robots has focused on locomotion in various environments. In this paper, a gait-generation algorithm for a mobile robot that can travel from the ground to a wall and climb vertical surfaces is proposed. The algorithm was inspired by a gecko lizard. Our gait planning was based on inverse kinematics using the Jacobian of the whole body, where the redundancy was solved by defining an object function for the gecko posture to avoid collisions with the surface. The optimal scalar factor for these two objects was obtained by defining a superior object function to minimize the angular acceleration of joints. The algorithm was verified through simulation of the gecko model travelling on given task paths and avoiding abnormal joint movements and collisions.     

Polychaete-Like Undulatory Robotic Locomotion in Unstructured Substrates

A biological paradigm of versatile locomotion and effective motion control is provided by the polychaete annelid worms, whose motion adapts to a large variety of unstructured environmental conditions (sand, mud, sediment, water, etc.), and could thus be of interest to replicate by robotic analogs. Their locomotion is characterized by the combination of a unique form of tail-to-head body undulations (opposite to snakes and eels), with the rowing-like action of numerous lateral appendages distributed along their long segmented body. Focusing on the former aspect of polychaete locomotion, computational models of crawling and swimming by such tail-to-head body undulations have been developed in this paper. These are based on the Lagrangian dynamics of the system and on resistive models of its interaction with the environment, and are used for simulation studies demonstrating the generation of undulatory gaits. Several biomimetic robotic prototypes have been developed, whose undulatory actuation achieves propulsion on sand and other granular unstructured environments. Extensive experimental studies demonstrate the feasibility of robot propulsion by tail-to-head body undulations in such environments, as well as the agreement of its qualitative and quantitative characteristics to the predictions of the corresponding computational models.     

Functional Redesign of Mantis 2.0, a Hybrid Leg-Wheel Robot for Surveillance and Inspection

The paper discusses the redesign of the second version of the Mantis hybrid leg-wheel mobile robot, conceived for surveillance and inspection tasks in unstructured indoor and outdoor environments. This small-scale ground mobile robot is characterized by a main body equipped with two front actuated wheels, a passive rear axle and two rotating legs. Motion on flat and even ground is purely wheeled in order to obtain high speed, high energetic efficiency and stable camera vision; only in case of obstacles or ground irregularities the front legs realize a mixed leg-wheel locomotion to increase the robot climbing ability; in particular, the outer profile of the legs, inspired by the praying mantis, is specially designed to climb square steps. The multibody simulations and the experimental tests on the first prototype have shown the effectiveness of the mixed leg-wheel locomotion not only for step climbing, but also on uneven and yielding terrains. Nevertheless, extensive experimental tests have shown that the front wheels may slip in the last phase of step climbing in case of contact with some materials. In order to overcome this problem, the leg design has been modified with the introduction of auxiliary passive wheels, which reduce friction between legs and step upper surface; these wheels are connected to the legs by one-way bearings, in order to rotate only when they are pulled by the front wheels, and remaining locked when they have to push forward the robot. The influence of the auxiliary wheels on the front wheels slippage is investigated by means of theoretical analysis and multibody simulations.     

Adaptive Robot Biped Locomotion with Dynamic Motion Primitives and Coupled Phase Oscillators

In order to properly function in real-world environments, the gait of a humanoid robot must be able to adapt to new situations as well as to deal with unexpected perturbations. A promising research direction is the modular generation of movements that results from the combination of a set of basic primitives. In this paper, we present a robot control framework that provides adaptive biped locomotion by combining the modulation of dynamic movement primitives (DMPs) with rhythm and phase coordination. The first objective is to explore the use of rhythmic movement primitives for generating biped locomotion from human demonstrations. The second objective is to evaluate how the proposed framework can be used to generalize and adapt the human demonstrations by adjusting a few open control parameters of the learned model. This paper contributes with a particular view into the problem of adaptive locomotion by addressing three aspects that, in the specific context of biped robots, have not received much attention. First, the demonstrations examples are extracted from human gaits in which the human stance foot will be constrained to remain in flat contact with the ground, forcing the “bent-knee” at all times in contrast with the typical straight-legged style. Second, this paper addresses the important concept of generalization from a single demonstration. Third, a clear departure is assumed from the classical control that forces the robot’s motion to follow a predefined fixed timing into a more event-based controller. The applicability of the proposed control architecture is demonstrated by numerical simulations, focusing on the adaptation of the robot’s gait pattern to irregularities on the ground surface, stepping over obstacles and, at the same time, on the tolerance to external disturbances.     

Exploiting natural dynamics for gait generation in undulatory locomotion

ABSTRACT

Robotic vehicles inspired by animal locomotion operate via periodic body movements. The pattern of body oscillation (gait) can be mimicked from animals, but understanding the principles underlying gait generation would allow for broad, flexible applications beyond nature's design. We hypothesise that travelling-wave oscillations observed in undulatory locomotion can be characterised as a natural oscillation of the locomotion dynamics and propose a formal definition of the natural gait for locomotion systems. We identify the essential dynamics and define the mode shape of natural oscillation by the free response of an idealised system. We then use body-environment resonance to define the amplitude and frequency. Explicit formulas for the natural gait are derived to provide insight into the mechanisms underlying undulatory locomotion. Examples of a swimming leech and a fictitious swimmer illustrate how undulatory gaits similar to those observed can be produced as the natural gait and modulated to achieve different swim speeds.     

Intelligent robots as artificial living creatures

This article introduces a multi locomotion robot, MLR III, which has multiple locomotion types, i.e., not only brachiating but also walking. Conventionally we have studied dexterous locomotion robots and their controller design. One is a simplified two-link robot, Brachiator II. This is an example of an underactuated system in which a robot mechanism has more degrees of freedom than actuators. The desired motions are encoded as the output of a target dynamical system inspired by the pendulum-link motion of an apes brachiation. The other is a monkey-type robot, Brachiator III. Brachiator III achieves a dexterous motion using redundant degrees of freedom. The motion is generated in an empirical learning process on an intelligent structure, on which the learning algorithm coordinates some primitive motions to generate the desired motion. MLR III is an extended locomotion robot that has multiple types of locomotions: brachiation, bipedal walking, and quadrupedal walking, similar to a monkey or gorilla. This article introduces the mechanism and controller design for brachiating motion.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robitics, Oita, Japan, January 24–26, 2003     

蛇形机器人侧向运动的研究

本文提出了一种新型蛇形机器人机构，建立了其空间运动学模型，实现了蛇形 机器人的两种侧向运动：侧向蜿蜒运动和侧向滚动，前者通过调节两个异相波的频率比，实 现了任意方向的侧向运动．后者通过控制运动波的幅值变化，实现了各种形式的纯侧向移动 ，当幅值足够大时，这种侧向滚动可以跨越障碍．     

An adaptive, self-organizing dynamical system for hierarchical control of bio-inspired locomotion

In this paper, dynamical systems made up of locally coupled nonlinear units are used to control the locomotion of bio-inspired robots and, in particular, a simulation of an insect-like hexapod robot. These controllers are inspired by the biological paradigm of central pattern generators and are responsible for generating a locomotion gait. A general structure, which is able to change the locomotion gait according to environmental conditions, is introduced. This structure is based on an adaptive system, implemented by motor maps, and is able to learn the correct locomotion gait on the basis of a reward function. The proposed control system is validated by a large number of simulations carried out in a dynamic environment for simulating legged robots.     

A comparison of three insect-inspired locomotion controllers

This paper compares three insect inspired controllers which were implemented on an autonomous hexapod robot. There is a growing interest in using insect locomotion schemes to control walking robots. Researchers' interest in insect-based controllers ranges from understanding the biological basis of locomotion control in insects to building real-time walking machines which require relatively little computational power. Several models for insect locomotion exist, and robotics researchers tend to adopt one approach and experiment with it.

In contrast, this paper offers a comparison of three insect inspired controllers — all of which were implemented and tested on the same autonomous hexapod robot. Some of the controllers used reflex-based mechanisms whereas others used pattern-based mechanisms. Reflexive controllers exploit sensory stimulus and response reactions to produce leg motion and gait coordination. In contrast, pattern-based controllers depend more upon pre-programmed patterns of behavior which may be influenced by external events. Typically, these pre-programmed patterns of behavior are implemented using central pattern generators (CPGs).

In this work, we compare gait coordination performance of three controllers on flat terrain. We extend the comparison to include leg loading considerations, disabled leg compensation, and externally applied leg perturbations. We discuss the differences between controllers with respect to inconsistent leg retraction velocities, leg design issues, sensing requirements, and computational issues. The robot performed quite differently under varying experimental conditions depending upon which controller was used. We found that controller performance was the most sensitive to robot design parameters. For our case, we had the most success with pattern-based mechanisms given the leg design of our robot and its limitations in controlling the retraction velocity of its legs. The pattern-based mechanisms allowed the robot to remain stable over a variety of gaits while the robot was subjected to loading the legs, disabling a leg, and physically disturbing the legs. The reflexive mechanisms were less successful at maintaining stability when the robot's legs were increasingly disrupted.     

Control of snake robots with switching constraints: trajectory tracking with moving obstacle

We propose control of a snake robot that can switch lifting parts dynamically according to kinematics. Snakes lift parts of their body and dynamically switch lifting parts during locomotion: e.g. sinus-lifting and sidewinding motions. These characteristic types of snake locomotion are used for rapid and efficient movement across a sandy surface. However, optimal motion of a robot would not necessarily be the same as that of a real snake as the features of a robot’s body are different from those of a real snake. We derived a mathematical model and designed a controller for the three-dimensional motion of a snake robot on a two-dimensional plane. Our aim was to accomplish effective locomotion by selecting parts of the body to be lifted and parts to remain in contact with the ground. We derived the kinematic model with switching constraints by introducing a discrete mode number. Next, we proposed a control strategy for trajectory tracking with switching constraints to decrease cost function, and to satisfy the conditions of static stability. In this paper, we introduced a cost function related to avoidance of the singularity and the moving obstacle. Simulations and experiments demonstrated the effectiveness of the proposed controller and switching constraints.     

Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

We investigate learning of flexible robot locomotion controllers, i.e., the controllers should be applicable for multiple contexts, for example different walking speeds, various slopes of the terrain or other physical properties of the robot. In our experiments, contexts are desired walking linear speed of the gait. Current approaches for learning control parameters of biped locomotion controllers are typically only applicable for a single context. They can be used for a particular context, for example to learn a gait with highest speed, lowest energy consumption or a combination of both. The question of our research is, how can we obtain a flexible walking controller that controls the robot (near) optimally for many different contexts? We achieve the desired flexibility of the controller by applying the recently developed contextual relative entropy policy search(REPS) method which generalizes the robot walking controller for different contexts, where a context is described by a real valued vector. In this paper we also extend the contextual REPS algorithm to learn a non-linear policy instead of a linear policy over the contexts which call it RBF-REPS as it uses Radial Basis Functions. In order to validate our method, we perform three simulation experiments including a walking experiment using a simulated NAO humanoid robot. The robot learns a policy to choose the controller parameters for a continuous set of forward walking speeds.     

Optimal design of type-2 and type-1 fuzzy tracking controllers for autonomous mobile robots under perturbed torques using a new chemical optimization paradigm

This paper addresses the tracking problem for the dynamic model of a unicycle mobile robot. A novel optimization method inspired on the chemical reactions is applied to solve this motion problem by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application.     

On the Improvement of Walking Performance in Natural Environments by a Compliant Adaptive Gait

It is a widespread idea that animal-legged locomotion is better than wheeled locomotion on natural rough terrain. However, the use of legs as a locomotion system for vehicles and robots still has a long way to go before it can compete with wheels and trucks, even on natural ground. This paper aims to solve two main disadvantages plaguing walking robots: their inability to react to external disturbances (which is also a drawback of wheeled robots); and their extreme slowness. Both problems are reduced here by combining: 1) a gait-parameter-adaptation method that maximizes a dynamic energy stability margin and 2) an active-compliance controller with a new term that compensates for stability variations, thus helping the robot react stably in the face of disturbances. As a result, the combined gait-adaptation approach helps the robot achieve faster, more stable compliant motions than conventional controllers. Experiments performed with the SILO4 quadruped robot show a relevant improvement in the walking gait     

仿蛇变体机器人运动机理研究

本文设计了一种蛇形机器人，分析了蛇形机器人的结构，详细讨论了蛇形机器人的运 动机理和几何结构关系，并推导出蛇形机器人的控制算法和相应的控制程序，蛇形机器人在 程序控制下能够向前、向后运动，在一定程度上实现了蛇的运动．     

带主动腰关节的四足机器人平稳运动控制

针对四足机器人在对角小跑运动时出现的后腿“拖地”、机体振荡的现象,提出了一种基于偏航方向上主动腰关节摆动的解决方法。通过D-H法对机器人各关节进行运动学建模,获得其运动学方程,并采用Kuramoto振荡器模型作为扩展的CPG耦合网络振子,实现对腰、腿关节的统一控制。仿真实验表明,经过腰关节控制优化后的机器人在对角小跑时,相对于刚体躯干的机器人,姿态角变化幅度显著减小,抬腿高度明显增加,有效地提高了机器人的运动稳定性,证明了方法的可行性。     

Controlling swimming and crawling in a fish robot using a central pattern generator

Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when the robot has to move in a complex environment with continuous variations of the speed, direction, and type of locomotor behavior. In this article we address the problem of controlling the non-steady state swimming and crawling of a novel fish robot. For this, we have designed a control architecture based on a central pattern generator (CPG) implemented as a system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. To test our controller, we designed BoxyBot, a simple fish robot with three actuated fins capable of swimming in water and crawling on firm ground. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light, water, and touch sensors. Results are presented demonstrating the agility of the robot and interesting properties of a CPG-based control approach such as stability of the rhythmic patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters. The robot is currently used in a temporary 20-month long exhibition at the EPFL. We present the hardware setup that was designed for the exhibition, and the type of interactions with the control system that allow visitors to influence the behavior of the robot. The exhibition is useful to test the robustness of the robot for long term use, and to demonstrate the suitability of the CPG-based approach for interactive control with a human in the loop. This article is an extended version of an article presented at BioRob2006 the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics.     

A method for determination of optimal gaits with application to a snake-like serial-link structure

In this paper, we present a method of determining optimal gaits for shape actuated locomotion systems. This method is the synthesis of techniques for computing reduced equations for robotic locomotion systems and a numerical optimal control strategy. Symmetry reduction processes induce a form of locomotion system dynamics that reveals a cyclic-like coupling between group, shape, and momenta coordinates. This form allows one to focus on designing gaits, abandoning concern over shape dynamics. Using this vantage point we indicate how a numerical optimal control method based on Gaussian quadrature may be acclimatized to periodicity, thus providing optimal gaits. The method is demonstrated by means of its application to a snake-like serial-link structure or snake robot. This application provides scientific merit to hypotheses concerning observed locomotion phenomena amongst animals employing undulatory propulsive mechanisms.     

Mechanical Design of a Trunk with Redundant and Viscoelastic Joints for Rhythmic Quadruped Locomotion

Passive mechanisms, such as free joints and viscoelastic components, enable natural oscillation of the robot body, which allows rhythmic locomotion with low energy and computational costs. In particular, joint viscoelasticity can be a powerful candidate for changing natural oscillation and so influence the operation performance of locomotion. The present study considers the passive mechanism of a trunk, and investigates the contributions of a trunk mechanism with redundant joints and tunable viscoelasticity to quadruped locomotion. A physical quadruped robot with a trunk mechanism is developed, and the walking performance of this robot for various gait patterns and joint viscoelasticities is investigated. A simulation model is also constructed based on the physical robot, and the contribution of the viscoelasticity to trunk oscillation and the appropriate joint viscoelasticity and number of trunk joints are discussed. Experimental results obtained using the physical robot indicate that the proposed trunk mechanism contributes to successful locomotion as compared to a robot with a rigid trunk and that the velocity is influenced by not only the gait pattern, but also the joint viscoelasticity (i.e., there are appropriate couplings of the joint viscoelasticity and gait pattern). The simulation results indicate that the trunk mechanism requires joint viscoelasticity in order to achieve oscillation and that a greater number of joints having a smaller joint viscoelasticity enables higher velocity. These results suggest that, in addition to the leg mechanism and the controller design, the design of the trunk mechanism is also important.     

NiTi形状记忆合金驱动的仿生鱼鳍的研究

为了提高仿鱼型推进器在水中运动的灵活性，选择了典型的依靠腹部绸带状鱼鳍波动运动产生推进力的黑色魔鬼刀鱼进行研究，对此绸带状鱼鳍的形态和运动机理进行了分析，同时对鱼鳍的结构进行简化．基于绸带状鱼鳍的这种简化模型设计了形状记忆合金驱动的仿生鱼鳍．介绍了鱼鳍的机械结构和相应的控制电路．重点推导了仿生鱼鳍波状运动时理论上能到达的推进速度和产生的推进力；并采用数值仿真给出了波动推进时仿生鱼鳍表面的压力分布以及推进力随时间的周期变化规律．将数值仿真结论和先前的实验结果进行了比较，验证了数值仿真的合理性和正确性．通过上述分析，说明基于形状记忆合金驱动的仿生鱼鳍的研究是很有意义而且可行的．