Localization and path planing

A system to cope with the problem of autonomous mobile robot navigation. It is able to perform path planning and localize the robot in the real world environment. The localization is first carried out using the known map, and the laser range scanner is then used to localize the robot based on t

Project Title

Localization and path planing

Project Area of Specialization

Robotics

Project Summary

A system to cope with the problem of autonomous mobile robot navigation. It is able to perform path planning and localize the robot in the real world environment. The localization is first carried out using the known map, and the laser range scanner is then used to localize the robot based on the Monte Carlo Localization technique. For the path planning, the visibility graph is established based on the current position of the robot. The RRT algorithm is then used to find the shortest path to the goal position.Accurate  localization of a vehicle is a fundamental challenge and one of the most important tasks of mobile robots. For autonomous navigation, motion tracking, and obstacle detection and avoidance, a robot must maintain knowledge of its position over time. Vision-based odometry is a robust technique utilized for this purpose. It allows a vehicle to localize itself robustly.

Project Objectives

A robust navigating robot which localize itself in the obtained map of the enviroment and plans a path to reach a goal.

Project Implementation Method

The platform for our project is Robot Operating system (ROS) .Initially,a map of unknown enviroment is saved with the help of data obtained from LiDAR mounted on top of robot then adaptive Monte Carlo Localization technique is used to localize the robot in this saved map.First global planner plans the path by using the RRT algorithm, then local planner models DWA used to follow or implement that path for robot to move at desired location in map. We are using the extremum seeking control  to control the motors and implement the cmd_vels received from dwa local planner.

Benefits of the Project

• Cost of human labour is reduced by using it as serving robot in restaurants 
• In emergency cases like corona virus spreading ,we can use self navigating robot to deliver medicines to persons where human can not go 
• For personal assistance in house held activities.

Technical Details of Final Deliverable

Navigation of robot by using Simultaneous Location and path planning (SLAM) :

• For navigation, motors are controlled by PI controller,odometry data from encoders to get wheel's velocities and position , this data is sent along with Laser scan data to obtain the map of continuosly moving robot then we get the pose by particle filter approach (AMCL)
• For path planning a local planner is used which works on DWA algorithm to autonomously move a robot to desired position.

Final Deliverable of the Project

Hardware System

Core Industry

Transportation

Other Industries

Medical , Agriculture , Security

Core Technology

Robotics

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com