CPG-Based Control Scheme for Quadruped Robot to Withstand the Lateral Impact
This addresses stability issues for quadruped robots in dynamic environments, but it is incremental as it builds on existing CPG and ZMP methods.
This paper tackles the problem of enabling quadruped robots to withstand lateral impacts by proposing a stability control strategy using an extended Central Pattern Generator (CPG) network and lateral trot gait. The result shows that the robot's ability to resist lateral impact increases by about 125%, from 0.72g to 1.55g.
This paper aims to present a stability control strategy for quadruped robot under lateral impact with the help of lateral trot. We firstly propose five necessary conditions for keeping balance. The classical four-neuron Central Pattern Generator (CPG) network with Hopf oscillators is then extended to eight-neuron network with four more trigger-enabled neurons, which controls the lateral trot. With proper adjustment of network's parameters, such network can coordinate the lateral and longitudinal trot gait. Based on Zero Movement Point (ZMP) theory, the robot is modeled as an inverted pendulum to plan the Center of Gravity (CoG) position and calculate the needed lateral step length. The simulation shows that the lateral acceleration of the quadruped robot after lateral impact regains to the normal range in a short time. Comparison shows that the maximal lateral impact that robot can resist increases about 125% from 0.72g to 1.55g.