Abstract
This work investigates locomotion efficiency optimization and adaptive path following of snake-like robots in a complex environment. To optimize the locomotion efficiency, it takes energy consumption and forward velocity into account to investigate the optimal locomotion parameters of snake-like robots controlled by a central pattern generator (CPG) controller. A cuckoo search (CS) algorithm is applied to optimize locomotion parameters of the robot for environments with variable fractions and obstacle distribution. An adaptive path following method is proposed to steer the snake-like robot forward and along a desired path. The efficiency and accuracy of the proposed path following method is researched. In addition, a control framework that includes a CPG network, a locomotion efficiency optimization algorithm, and an adaptive path following method is designed to control snake-like robots move in different environments. Simulation and experimental results are presented to illustrate the performance of the proposed locomotion optimization method and adaptive path following controller for snake-like robots in complexity terrains.
Highlights
Inspired by biological snakes, snake-like robots have received significant attention to take the place of human work in some special situations such as exploration, monitoring, and surveillance tasks [1]
To test the performance of the locomotion efficiency optimization method proposed in Section 3 and the adaptive line of sight (LOS) path following control scheme described in Section 4, we have conducted extensive simulations
A Hopf central pattern generator (CPG) network is used to replace the serpentine function to generate reference functions of joints of a snake-like robot to improve the smooth degree of control signal
Summary
Snake-like robots have received significant attention to take the place of human work in some special situations such as exploration, monitoring, and surveillance tasks [1]. Some important performances such as locomotion efficiency and path following accuracy of snake-like robots are not considered in these studies. A framework is researched to optimize locomotion of underwater snake robots and their energy efficiencies are investigated in [27]. The energy consumption and forward speed are taken into account to investigate the optimal gait parameters. Direction and forward velocity, efficiency, and error accumulation of snake-like robots are taken into account in the control of path following. A control framework includes a Hopf CPG network, an exponentially stable controller, a locomotion efficiency optimization algorithm, and an adaptive path following method. This work includes more accurate and detailed simulation and experiment results about efficiency optimization and adaptive path following in complex environments.
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