Performance measures for locomotion robots

We design two performance measures for a planar locomotion robot, modeled closely after the Platonic Beast. The first measure is proportional to the total motion of all joints during locomotion of the robot. This is a rough approximation to the energy consumption of the robot. The second measure determines the maximal speed of locomotion, for given limits on the joint speeds. We compute optimal modes of locomotion on different slopes for various designs. The results indicate that a variable link length can greatly improve the ability of the robot to walk on steep slopes. © 1997 John Wiley & Sons, Inc.     

Development of virtual link method for the solution of hyper-redundant spatial robots

This article presents a new method for the kinematics of hyper-redundant spatial robots, called the virtual link method. The method is based on dividing the robot into sub-systems consisting of three or four links. Virtual links are established between the first and the last nodes of each sub-system. A hypothetical robot with reduced of degrees of freedom is developed using the virtual links. The method then solves for the kinematics of the virtual link system followed by the sub-systems. The virtual link method also provides a singularity-free solution by predicting their occurrence and taking appropriate action. An approaching singularity is reflected by a drop in the determinant of the Jacobian of the system below a threshold value. In this situation, the method either chooses a different virtual link configuration or switches to a displacement distribution scheme. © 1996 John Wiley & Sons, Inc.     

Two trajectory tracking control methods for space hyper-redundant cable-driven robots considering model uncertainty

Multibody System Dynamics - Space hyper-redundant cable-driven robots (SHCDRs) have a slender body structure and high dexterity, which is very suitable for complex and limited unstructured space...     

Clock-turning gait synthesis for humanoid robots

Turning gait is a basic motion for humanoid robots. This paper presents a method for humanoid tuming, i.e. clock-turning. The objective of clock-turning is to change robot direction at a stationary spot. The clock-turning planning consists of four steps： ankle trajectory generation, hip trajectory generation, knee trajectory generation, and inverse kinematics calculation. Our proposed method is based on a typical humanoid structure with 12 DOFs （degrees of freedom）. The final output of clock-turning planning is 12 reference trajectories, which are used to control a humanoid robot with 12 DOFs. ZMP （zero moment point） is used as stability criterion for the planning. Simulation experiments are conducted to verify the effectiveness of our proposed clock-turuing method.     

A hyper-redundant manipulator

“Hyper-redundant” manipulators have a very large number of actuatable degrees of freedom. The benefits of hyper-redundant robots include the ability to avoid obstacles, increased robustness with respect to mechanical failure, and the ability to perform new forms of robot locomotion and grasping. The authors examine hyper-redundant manipulator design criteria and the physical implementation of one particular design: a variable geometry truss     

A versatile locomotion mechanism for amphibious robots: eccentric paddle mechanism

Most of recently developed rescue robots can only be deployed to limited attacked regions after tsunami and the floods, due to their limited mobility on complex amphibious terrains. To access such amphibious environments with improved mobility, we propose a novel eccentric paddle mechanism (ePaddle) which has a set of paddles eccentrically placed in a wheel to perform multiple terrestrial, aquatic, and amphibious gaits. One of the advantages of our proposed ePaddle mechanism is its unique locomotion versatility introduced by the eccentric distance between the paddle shaft and the wheel center. We demonstrate this versatility by proposing five typical gaits for traveling on different terrains. For instance, wheeled rolling gait is used to achieve high-speed locomotion on even terrain. Legged gait is applied to travel on the rough terrains. To access the soft terrains where wheels slip and legs sink, a wheel-leg-integrated gait is performed by digging the paddle into the ground. To swim in the water, rotational paddling and oscillating paddling gaits are proposed. For each of these gaits, standard gait sequence is defined and joint parameters are calculated based on kinematics. An ePaddle prototype is then built and tested with the proposed gait sequences. Experimental results verify the design of the ePaddle mechanism as well as its versatile gaits.     

Emergent synthesis of motion patterns for locomotion robots

Emergence of stable gaits in locomotion robots is studied in this paper. A classifier system, implementing an instance-based reinforcement-learning scheme, is used for the sensory-motor control of an eight-legged mobile robot and for the synthesis of the robot gaits. The robot does not have a priori knowledge of the environment and its own internal model. It is only assumed that the robot can acquire stable gaits by learning how to reach a goal area. During the learning process the control system is self-organized by reinforcement signals. Reaching the goal area defines a global reward. Forward motion gets a local reward, while stepping back and falling down get a local punishment. As learning progresses, the number of the action rules in the classifier systems is stabilized to a certain level, corresponding to the acquired gait patterns. Feasibility of the proposed self-organized system is tested under simulation and experiment. A minimal simulation model that does not require sophisticated computational schemes is constructed and used in simulations. The simulation data, evolved on the minimal model of the robot, is downloaded to the control system of the real robot. Overall, of 10 simulation data seven are successful in running the real robot.     

Design and control of tensegrity robots for locomotion

The static properties of tensegrity structures have been widely appreciated in civil engineering as the basis of extremely lightweight yet strong mechanical structures. However, the dynamic properties and their potential utility in the design of robots have been relatively unexplored. This paper introduces robots based on tensegrity structures, which demonstrate that the dynamics of such structures can be utilized for locomotion. Two tensegrity robots are presented: TR3, based on a triangular tensegrity prism with three struts, and TR4, based on a quadrilateral tensegrity prism with four struts. For each of these robots, simulation models are designed, and automatic design of controllers for forward locomotion are performed in simulation using evolutionary algorithms. The evolved controllers are shown to be able to produce static and dynamic gaits in both robots. A real-world tensegrity robot is then developed based on one of the simulation models as a proof of concept. The results demonstrate that tensegrity structures can provide the basis for lightweight, strong, and fault-tolerant robots with a potential for a variety of locomotor gaits.     

Multimode locomotion via SuperBot reconfigurable robots

One of the most challenging issues for a self-sustaining robotic system is how to use its limited resources to accomplish a large variety of tasks. The scope of such tasks could include transportation, exploration, construction, inspection, maintenance,in-situ resource utilization, and support for astronauts. This paper proposes a modular and reconfigurable solution for this challenge by allowing a robot to support multiple modes of locomotion and select the appropriate mode for the task at hand. This solution relies on robots that are made of reconfigurable modules. Each locomotion mode consists of a set of characteristics for the environment type, speed, turning-ability, energy-efficiency, and recoverability from failures. This paper demonstrates a solution using the SuperBot robot that combines advantages from M-TRAN, CONRO, ATRON, and other chain-based and lattice-based robots. At the present, a single real SuperBot module can move, turn, sidewind, maneuver, and travel on batteries up to 500 m on carpet in an office environment. In physics-based simulation, SuperBot modules can perform multimodal locomotions such as snake, caterpillar, insect, spider, rolling track, H-walker, etc. It can move at speeds of up to 1.0 m/s on flat terrain using less than 6 W per module, and climb slopes of no less 40 degrees. Harris Chi Ho Chiu is a PhD Student in Computer Science at the University of Southern California and a research assistant in Polymorphic Robotics Laboratory of Information Science Institute. He received his Master in Computer Science from the University of Southern California and his Bachelor of Engineering from the University of Hong Kong. His research interests include intelligent automated systems, modular self-reconfigurable systems, artificial intelligence, and machine learning. Michael Rubenstein is currently a PhD student at the Polymorphic Robotics Laboratory, working on the CONRO and Superbot self-reconfigurable robotic systems. He has received his bachelors in Electrical Engineering from Purdue University, and his masters in Electrical Engineering from the University of Southern California, and is currently working towards his PhD in Computer Science from the University of Southern California. His interests include modular self-reconfigurable systems, autonomous robots, self-healing systems, and self-replicating systems. Jagadesh B Venkatesh is a member of the Polymorphic Robotics Laboratory at the Information Sciences Institute. He is currently a Master’s candidate in the Product Development Engineering program at the University of Southern California. He received his MS in Computer Science with specialization in Intelligent Robotics, also at the University of Southern California in 2005. His current interest is the commercialization of robotic technologies, specifically in the consumer robotics sector.     

A distributed and morphology-independent strategy for adaptive locomotion in self-reconfigurable modular robots

In this paper, we present a distributed reinforcement learning strategy for morphology-independent life-long gait learning for modular robots. All modules run identical controllers that locally and independently optimize their action selection based on the robot’s velocity as a global, shared reward signal. We evaluate the strategy experimentally mainly on simulated, but also on physical, modular robots. We find that the strategy: (i) for six of seven configurations (3–12 modules) converge in 96% of the trials to the best known action-based gaits within 15 min, on average, (ii) can be transferred to physical robots with a comparable performance, (iii) can be applied to learn simple gait control tables for both M-TRAN and ATRON robots, (iv) enables an 8-module robot to adapt to faults and changes in its morphology, and (v) can learn gaits for up to 60 module robots but a divergence effect becomes substantial from 20–30 modules. These experiments demonstrate the advantages of a distributed learning strategy for modular robots, such as simplicity in implementation, low resource requirements, morphology independence, reconfigurability, and fault tolerance.     

A novel compound biped locomotion algorithm for humanoid robots to realize biped walking

In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.     

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.     

Energy-optimal gait analysis of quadruped robots

It is important for walking robots such as quadruped robots to have an efficient gait. Since animals and insects are the basic models for most walking robots, their walking patterns are good examples. In this study, the walking energy consumption of a quadruped robot is analyzed and compared with natural animal gaits. Genetic algorithms have been applied to obtain the energy-optimal gait when the quadruped robot is walking with a set velocity. In this method, an individual in a population represents the walking pattern of the quadruped robot. The gait (individual) which consumes the least energy is considered to be the best gait (individual) in this study. The energy-optimal gait is analyzed at several walking velocities, since the amount of walking energy consumption changes if the walking velocity of the robot is changed. The results of this study can be used to decide what type of gait should be generated for a quadruped robot as its walking velocity changes. This work was presented, in part, at the Sixth International Symposium on Artificial Life and Robotics, Tokyo, Japan, January 15–17, 2001.     

A simple approach to the control of locomotion in self-reconfigurable robots

In this paper we present role-based control which is a general bottom-up approach to the control of locomotion in self-reconfigurable robots. We use role-based control to implement a caterpillar, a sidewinder, and a rolling track gait in the CONRO self-reconfigurable robot consisting of eight modules. Based on our experiments and discussion we conclude that control systems based on role-based control are minimal, robust to communication errors, and robust to reconfiguration.     

A new spatial hyper-redundant manipulator

This work presents a novel hyper-redundant manipulator. Such a manipulator is built with a variable number of tandem-assembled modules. Each module consists of a 3-dof parallel manipulator with asymmetric extremities in which moving platform possesses mixed motions with respect to the base platform. The manipulator's architecture is so simple that the forward position analysis is presented in closed-form solution, more specifically, in echelon-form solution. On the other hand, the velocity and acceleration analyses are carried out using the theory of screws. Finally, a case study consisting of solving the kinematic analysis of a 30-dof hyper-redundant manipulator is presented.     

A method of gait coordination of hexapod robots using immune networks

Biological information processing systems can be regarded as one of the ultimate decentralized systems, and have been expected to provide various fruitful ideas in the engineering field. Among these systems, the immune system plays an important role in coping with dynamically changing environments by constructing self-nonself recognition networks among different species of antibodies, and has many interesting features from an engineering stand-point, such as learning, self-organizing abilities, and so on. However, it has not yet been applied to engineering fields. Therefore we pay close attention to the immune system and attempt to construct an artificial immune network for robot control. In this study we propose a new interpretation of the roles of antibodies in terms of self-assertion and subordination, and apply this idea to a gait coordination problem of a hexapod robot as a practical example. Several computer simulations are carried out, and the robustness against disturbances and the feasibility of our method are confirmed. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

A variational approach to path planning for hyper-redundant manipulators

Motion planning for hyper-redundant manipulators in a complicated and cluttered workspace is a challenging problem. Many of the path planning algorithms, based on cell decomposition or potential field, fail due to the high dimensionality and complex nature of the C-space. Probabilistic roadmap methods (PRM) which have been proven to be successful in high dimensional C-spaces suffer from the drawback of generating paths which involve a lot of redundant motion. In this paper, we propose a path optimizing method to improve a given path in terms of path length and the safety against the collisions, using a variational approach. The capability of variational calculus to optimize a path is demonstrated on a variety of examples. The approach succeeds in providing a good quality path even in high dimensional C-spaces.     

Central pattern generators based on Matsuoka oscillators for the locomotion of biped robots

Biologically inspired control approaches based on central pattern generators (CPGs) with neural oscillators have been drawing much attention for the purpose of generating rhythmic motion for biped robots with human-like locomotion. This article describes the design of a neural-oscillator-based gait-rhythm generator using a network of Matsuoka oscillators to generate a walking pattern for biped robots. This includes the proper consideration of the oscillator’s parameters, such as a time constant for the adaptation rate, coupling factors for mutual inhibitory connections, etc., to obtain a stable and desirable response from the network. The article examines the characteristics of a CPG network with six oscillators, and the effect of assigning symmetrical and asymmetrical coupling coefficients among oscillators within the network structure under different possible inhibitions and excitations. The kinematics and dynamics of a five-link biped robot have been modeled, and its joints are actuated through simulation by the torques output from the neural rhythm generator to generate the trajectories for hip, knee, and ankle joints. The parameters of the neural oscillators are tuned to achieve flexible trajectories. The CPG-based control strategy is implemented and tested through a simulation. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Evolution of side-winding locomotion of simulated limbless, wheelless robots

Inspired by the efficient method of locomotion of the rattlesnake Crotalus cerastes, the objective of this work was the automatic design through genetic programming of the fastest possible, side-winding locomotion of simulated limbless, wheelless artifacts. The realism of the simulation is ensured by employing open dynamics engine (ODE), which allows accounting for all the physical forces resulting from the actuators (muscles), friction, gravity, collisions, and joint constraints. The empirically obtained results demonstrate that the complex side-winding locomotion emerges from relatively simple motion patterns of morphological segments (vertebrae). The robustness of automatically evolved locomotion is verified by (i) the reasonable performance degradation when partial damage to the artifact is inflicted, and (ii) the ability to tackle obstacles. Contributing to the better understanding of the unique, side-winding locomotion, this work could be considered as a step toward building real limbless, wheelless robots, featuring unique engineering characteristics, which are able to perform robustly in difficult environments.This work was presented, in part, at the 9th International Symposium on Artificial Life and Robotics, Oita, Japan, January 28–30, 2004