Man-robot Communion Navigation Technology Based On Layered Costmap For Mobile Robot

The mobile robot navigation technology in the environment of man-robot communion is the development direction of the mobile robot research field.Using this technology,the robot can use the sensor information to perceive the surrounding environment and drive the robot to execute corresponding movement instructions,so that the robot can ensure collision-free during the movement process.Under the premise,maximize human comfort.The main research contents of this topic include the creation of high-matching layered costmaps,cognitive behavioral inference methods based on collision cost models,human-aware navigation algorithms and related experimental research.In this paper,we first create a highly-matched multi-layered cost map,which makes the placement of obstacles more accurate by updating the position of obstacles in real time,improves the match between the map and the real environment,and achieves the effect of "what you see is what you get" for environmental obstacles.Secondly,by reducing the number of unnecessary static obstacle updates,and adopting the isometric expansion method to optimize the data structure,the update speed of the cost map is improved;Secondly,in order to make robots perceive the human private space and sports trend,the mobile robot's perception of pedestrian behavioral intentions is developed.Lidar and Kinect sensors are used together to perform human detection to improve accuracy;a collision cost model is proposed in private space perception,so that the personal space that a person needs to be respected by the robot can be based on the collision probability between the robot and the human.Change and change;in the movement trend perception,this article uses the uniform velocity model to predict the human trajectory,so that the robot can make decisions in advance so as not to interfere with the human path;Finally,this paper creates behavior intentions based on layered costmaps.The knowledge layer as a carrier combines the space and movement trends of pedestrians with the value of multi-dimensional cost maps.Then,this paper studies a human-aware navigation algorithm,which can improve the performance of path planning,while improving human comfort and comply with certain social rules.This paper designs four modes for navigation technology to maximize the stability and reliability of the robot in the moving process.Firstly,the dynamic triangular window velocity planning method is proposed,and the optimal trajectory corresponding to the speed control command is obtained by designing the trajectory optimization equation.This method fully considers the performance of the motor and can make the robot plan a trajectory that conforms to human comfort.Finally,an experimental study of related algorithms was conducted.In this paper,experiments on layered costmaps,robots' perceptions of behavioral intentions of pedestrians,and navigation of robots in human environments are conducted.The experimental results show that high matching and real-time performance meet the requirements,human space and movement trends can be reflected in layered costmaps,and robots can effectively navigate and improve human comfort in a dynamic human environment.