Adaptive Dynamic Walking of a Quadruped Robot on Irregular Terrain Based on Biological Concepts

Abstract

We have been trying to induce a quadruped robot to walk with medium walking speed on irregular terrain based on biological concepts. We propose the necessary conditions for stable dynamic walking on irregular terrain in general, and we design the mechanical system and the neural system by comparing biological concepts with those necessary conditions described in physical terms. A PD controller at the joints can construct the virtual spring-damper system as the visco-elasticity model of a muscle. The neural system model consists of a central pattern generator (CPG) and reflexes. A CPG receives sensory input and changes the period of its own active phase. The desired angle and P-gain of each joint in the virtual springdamper system is switched based on the phase signal of the CPG. CPGs, the motion of the virtual spring-damper system of each leg and the rolling motion of the body are mutually entrained through the rolling motion feedback to CPGs, and can generate adaptive walking. We report on our experimental results of dynamic walking on terrains of medium degrees of irregularity in order to verify the effectiveness of the designed neuro-mechanical system. We point out the trade-off problem between the stability and the energy consumption in determining the cyclic period of walking on irregular terrain, and we show one example to solve this problem. MPEG footage of these experiments can be seen at http://www.kimura.is.uec.ac.jp.

A gait transition algorithm based on hybrid walking gait for a quadruped walking robot

“…To develop a GT algorithm for the quadruped robot, the GT pattern of animal locomotion is analyzed and simpli- 5 Horse's gait transition from walk to trot [20] fied based on the HW gait as shown in Fig. 6.…”

“…Matsuoka studied a network of neurons with the ability mutually inhibit one another [3,4]. Fukuoka and Kimura successfully controlled a quadruped robot named "Tekken" over several types of terrain using a network of four Matsuoka oscillators [5,6]. Bailey studied controlling insect locomotion [7] and Liu et al studied controlling an AIBO robot [8].…”

Variable Stiffness Legs for Robust, Efficient, and Stable Dynamic Running

“…Inspired by Raibert's work on simple dynamic hopping robots [5], mechanical leg springs have been incorporated into a number of legged platforms, including the Scout [7,8], Tekken [24], Kolt [25], Whegs [26,27], Sprawlita [28], and RHex [29].…”

Gait Generation of Multilegged Robots by using Hardware Artificial Neural Networks

“…Living organisms autonomously operate under the control of small-sized neural networks. Therefore, researchers have begun studying artificial neural networks (ANNs) for robot control [6][7][8][9][10]. Biological neural networks are universally characterized by oscillatory patterns of electrical activity.…”

“…Famous class II neuron models include the Hodgkin-Huxley model [14] and Bonhoeffer-van der Pol model [15], mathematical neuron models that form the basis of bioinspired oscillatory pattern generation [16][17][18]. Most of the central pattern generators (CPGs) designed for the synchronized locomotion control of multilegged robots [6][7][8] are also constructed by mathematical neuron models. A CPG model using mathematical neuron models can be implemented on a field programmable gate array (FPGA).…”