Research On Environment Perception And Static Gait Planning Of Quadruped Robot Based On RGB-D Camera

Legged robots rely on discrete support point movements.Compared with wheeled,creeping,crawler and other movement methods,legged robots have lower requirements on the ground and more flexible.Among the legged robots,the quadruped robot avoids the redundancy of the mechanism while ensuring stability,which is one of the hotspots in robot research.In this paper,the RGB-D camera is selected as the main external environmental sensor for the application requirements of the quadruped robot in the indoor environment,to study the environmental perception and gait planning algorithm of the quadruped robot.The main research contents are as follows:First,based on the visual SLAM algorithm,the characteristics of the indoor environment are analyzed,and a visual front end combining visual feature points and planar features in the environment is proposed to study the extraction and matching of point and surface features,as well as motion solving algorithms.According to the characteristics of the visual odometer,the back-end optimization algorithm based on the pose map is selected to design the loop closing and the RGB-D SLAM algorithm design is completed.The experiments verify that the combination of point and surface features can effectively enhance the robustness of the SLAM algorithm.Second,study the gait planning of the quadruped robot,analyze its kinematics model,and construct the forward and inverse kinematic equations of the quadruped robot.Taking the stability margin as the benchmark,a discontinuous static gait of a four-legged robot is proposed,including the trajectory planning of the center of gravity of the robot and the trajectory planning of the swinging foot end.The stability of the four-legged robot during the static gait movement is verified through experiments.Thirdly,combining the point cloud map generated by the visual SLAM algorithm with the static gait of the quadruped robot,a robot path planning algorithm based on the point cloud map is proposed.Convert the point cloud map to an elevation grid map to distinguish the robot's movable area.Quantify terrain features from the perspective of the impact of terrain features on footing quality,design terrain cost functions,convert point cloud maps to terrain cost maps,design robot body center search algorithms on terrain cost maps,plan robot movement paths based on stability constraints,The feasibility of the robot path planning algorithm is verified through experiments.