Research On The Design And Path Planning Of A ROS Based Mobile Robot

With the rapid development of global technology,the intelligent application and research of robots have been recognized by various industries.Autonomous mobile robot technology has become the focus of research in this field,in which mobile robot chassis design,map construction,positioning and navigation have become the core issues of mobile robots.Autonomous mobile robots have a wide range of applications and can largely replace people in corresponding work,and then people are facing indispensable tools for complex scenarios,which has great research value and significance.However,mobile robots still have problems: how to design the robot's chassis and steering mechanism to improve the autonomous ability of the robot;how to use low-cost radar and depth cameras to build accurate maps,and encounter obstacles below the radar scanning plane,and the radar cannot Recognition;how to efficiently execute path planning algorithms based on the constructed map,autonomous positioning and navigation,and reach the corresponding target point;how to reduce the research and development cycle and labor cost of autonomous mobile robots.Aiming at the above-mentioned problems,through the investigation of domestic and foreign research status,a robot design scheme of Ackerman chassis and steering mechanism is finally determined,and the design parameters of the mobile robot are obtained through the analysis of the investigation.In Solid Works,the three-dimensional modeling,assembly and motion simulation testing of the whole and parts are carried out,and the mathematical model of the steering mechanism and the overall kinematics model of the mobile robot is established,and the MATLAB tool is used to optimize the analysis.Under the ROS system,software framework construction is carried out,in which simultaneous localization and mapping(SLAM)in unknown environments,path planning is the key to autonomous navigation of mobile robots.Using single-line lidar and depth camera for data fusion to realize SLAM technology;the existing basic rapid expansion random tree to solve the shortcomings and shortcomings of the planned path are described in detail.For the algorithm,there are random expansion and path in the two-dimensional grid map The problem of tortuosity,combined with the kinematic non-integrity constraints of mobile robot chassis and environmental condition constraints,proposes an improved fast-expansion stochastic algorithm.The improved algorithm effectively expands to the target point and uses a cubic uniform B-spline curve to simulate the polyline Together,the smoothness of the planned path is improved,and the improved algorithm is simulated and verified using MATLAB software.Finally,the improved algorithm is verified with the help of Rviz and Gazebo simulation environments in ROS.Finally,under the ROS architecture,part of the source code in the open source package is modified and the improved algorithm is inserted into the navigation framework in the form of a plug-in,and an actual test environment is built to validate the algorithm on the actual mobile robot.