The effect of mechanism design on the performance of a quadruped walking machine

The objective of this paper is to investigate the effect of mechanism design on the performance of a quadruped walking machine. For studying the effect of mechanism design on the performance of a quadruped walking machine, four designs with different crank and leg arrangements are proposed and analyzed. The performance of the walking machine, including the stance leg sequence, foot trajectory, pitch angle, and dynamic response of the quadruped walking machine are investigated and compared with the existing design. The results show that the phrase angle between front and rear legs on the same side should be 0° or 90° and the one between the legs on the different sides should be 180°. And, the design with the front and rear legs bent in the same direction has better performance in dynamic responses. The results of this study can serve as a reference for future design and optimization of quadruped walking machines

The effect of mechanism design on the performance of a quadruped walking machine

The objective of this paper is to investigate the effect of mechanism design on the performance of a quadruped walking machine. For studying the effect of mechanism design on the performance of a quadruped walking machine, four designs with different crank and leg arrangements are proposed and analyzed. The performance of the walking machine, including the stance leg sequence, foot trajectory, pitch angle, and dynamic response of the quadruped walking machine are investigated and compared with the existing design. The results show that the phrase angle between front and rear legs on the same side should be 0° or 90° and the one between the legs on the different sides should be 180°. And, the design with the front and rear legs bent in the same direction has better performance in dynamic responses. The results of this study can serve as a reference for future design and optimization of quadruped walking machines

Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation

An originally chaotic system can be controlled into various periodic dynamics. When it is implemented into a legged robot's locomotion control as a central pattern generator (CPG), sophisticated gait patterns arise so that the robot can perform various walking behaviors. However, such a single chaotic CPG controller has difficulties dealing with leg malfunction. Specifically, in the scenarios presented here, its movement permanently deviates from the desired trajectory. To address this problem, we extend the single chaotic CPG to multiple CPGs with learning. The learning mechanism is based on a simulated annealing algorithm. In a normal situation, the CPGs synchronize and their dynamics are identical. With leg malfunction or disability, the CPGs lose synchronization leading to independent dynamics. In this case, the learning mechanism is applied to automatically adjust the remaining legs' oscillation frequencies so that the robot adapts its locomotion to deal with the malfunction. As a consequence, the trajectory produced by the multiple chaotic CPGs resembles the original trajectory far better than the one produced by only a single CPG. The performance of the system is evaluated first in a physical simulation of a quadruped as well as a hexapod robot and finally in a real six-legged walking machine called AMOSII. The experimental results presented here reveal that using multiple CPGs with learning is an effective approach for adaptive locomotion generation where, for instance, different body parts have to perform independent movements for malfunction compensation.Comment: 48 pages, 16 figures, Information Sciences 201

Fast and Continuous Foothold Adaptation for Dynamic Locomotion through CNNs

Legged robots can outperform wheeled machines for most navigation tasks across unknown and rough terrains. For such tasks, visual feedback is a fundamental asset to provide robots with terrain-awareness. However, robust dynamic locomotion on difficult terrains with real-time performance guarantees remains a challenge. We present here a real-time, dynamic foothold adaptation strategy based on visual feedback. Our method adjusts the landing position of the feet in a fully reactive manner, using only on-board computers and sensors. The correction is computed and executed continuously along the swing phase trajectory of each leg. To efficiently adapt the landing position, we implement a self-supervised foothold classifier based on a Convolutional Neural Network (CNN). Our method results in an up to 200 times faster computation with respect to the full-blown heuristics. Our goal is to react to visual stimuli from the environment, bridging the gap between blind reactive locomotion and purely vision-based planning strategies. We assess the performance of our method on the dynamic quadruped robot HyQ, executing static and dynamic gaits (at speeds up to 0.5 m/s) in both simulated and real scenarios; the benefit of safe foothold adaptation is clearly demonstrated by the overall robot behavior.Comment: 9 pages, 11 figures. Accepted to RA-L + ICRA 2019, January 201

Combining series elastic actuation and magneto-rheological damping for the control of agile locomotion

All-terrain robot locomotion is an active topic of research. Search and rescue maneuvers and exploratory missions could benefit from robots with the abilities of real animals. However, technological barriers exist to ultimately achieving the actuation system, which is able to meet the exigent requirements of these robots. This paper describes the locomotioncontrol of a leg prototype, designed and developed to make a quadruped walk dynamically while exhibiting compliant interaction with the environment. The actuation system of the leg is based on the hybrid use of series elasticity and magneto-rheological dampers, which provide variable compliance for natural-looking motion and improved interaction with the ground. The locomotioncontrol architecture has been proposed to exploit natural leg dynamics in order to improve energy efficiency. Results show that the controller achieves a significant reduction in energy consumption during the leg swing phase thanks to the exploitation of inherent leg dynamics. Added to this, experiments with the real leg prototype show that the combined use of series elasticity and magneto-rheologicaldamping at the knee provide a 20 % reduction in the energy wasted in braking the knee during its extension in the leg stance phase

Optimum Gait Selection for Quadruped Robots

This paper studies periodic gaits of quadruped animals and its application to multilegged artificial locomotion systems. The purpose is to determine the best set of gait and locomotion variables during walking, for different robot velocities and intrabody compliance characteristics, based on two formulated performance measures. A set of experiments reveals the influence of the gait and locomotion variables upon the proposed indices, namely that the gait and the locomotion parameters should be adapted to the robot forward velocity and to the robot intra-body compliance characteristics.N/