Landing Point Planning And Foot Pattern Design Of Hexapod Robot

Legged robots have excellent terrain adaptability and multi-tasking capabilities,and have broad application prospects in many fields such as military,exploration,and rescue.Especially in the face of complex field environment operations,foot robots are the most effective solution compared to other types of mobile equipment.In order to give full play to the complex terrain movement capabilities of legged robots,a highly sophisticated motion control system and high-performance body components are required.In highly complex terrain,reasonable landing planning is a necessary condition to ensure the smooth movement of the legged robot.The foot end is the only interface between the robot and the ground,and its performance is the key factor affecting the selection of the landing point.Based on the performance of the foot end,this paper studies the landing point planning of legged robots for high-steep and rugged terrain,and optimizes foot attachment performance.Firstly,the constraints of the motion performance of the foot on the robot's motion ability are considered.The whole structure,leg configuration and key structure of the foot are analyzed,and the geometric model of the legged robot walking on rugged terrain is established.On this basis,the solution method of the grounding angle based on the single leg inverse kinematics is proposed.Considering the leg compensation angle,the " desired position" of the landing point is defined,and the leg compensation angle is calculated.The influence of landing point on the touchdown angle is summarized through simulation calculation,which is to prepare for subsequent landing point planning.Then,the constraints of the attachment performance of the foot on the robot's motion ability are considered.The force analysis of the robot body,leg drive and foot end is carried out,with the constraints of the fuselage force balance,the reasonable load of the drive and the effective support of the foot end,the maximum ratio of tangential force to normal force is minimized as the optimization target,and the foot force distribution model is established.Based on the standard particle swarm optimization(PSO),a multi-strategy improved particle swarm optimization(MPSO)algorithm is proposed.The penalty function is used to deal with the optimization model constraints to establish the fitness evaluation function,and the optimal force allocation optimization model is solved to prepare for the subsequent landing point planning.Finally,based on the previous research,the relationship between the landing point and the touchdown angle,the foot force and the stability of the legged robot is analyzed,and the feasibility judgment standard of the landing point is given.Considering the contact state,stability margin and sliding risk of the robot,a landing point evaluation function is constructed.A landing point planning method for high-steepness rugged terrain is proposed to improve the traveling performance of the legged robot in high-steepness rugged terrain.In addition,in order to further improve the traveling performance of the legged robot in complex terrain,the optimization of foot attachment performance is carried out.A finite element simulation model of the interaction between the sole and the ground is established.Based on the simulation model,a multiple quadratic regression model between the adhesion coefficient of the sole and the structural parameters of the sole pattern is established by using the central composite experimental design combined with the response surface method.Furthermore,the optimal design model of plantar adhesion performance was established,and the plantar pattern structure was optimized by the optimization method.The optimized plantar adhesion performance was improved.The research results have a positive guiding significance for the complex terrain motion planning and foot structure design of the legged robot,and provide a reference for further research on how to improve the complex terrain traveling ability of the legged robot.