Autonomous Obstacle Avoidance Robot Using ROS, Lidar, and Raspberry Pi with Matlab Path Planning

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OBSTACLE AVOIDANCE ROBOT
USING ROS & LIDAR WITH
RASPBERRY PI, MATLAB
 
OBSTACLE AVOIDANCE ON LONG DISTANCE
WITH PATH PLANNING
 
INTRODUCTION
 
Obstacle avoiding methods are used from least to the ultimate models. It is
used to avoid the collision on obstacles.
But before in old methods, there is no autonomous option to choose the
alternative path when the obstacle is present in the way. But this can be
possible now by using LIDAR with ROS, by using LIDAR scans mapping is done.
So that the Bot knows the complete map of the environment and by using PRM
for Path planning algorithm in Matlab alternative path can be chosen.
 
ABOUT MATLAB ROS
 
In the Latest version of Matlab, it has ROS (Robotic
Operating System) software supporting package. By using
that its system can able to communicate with the ROS robot
using ROS Network configurations.
 
EXISTING SYSTEM
 
In the existing obstacle avoidance robot, simply the
sensors like IR and Ultrasonic sensors are used to
sense the obstacle. It doesn’t have a feature to
choose the alternative path and to follow it.
 
PROPOSED SYSTEM
 
In this proposed system, by using 60-degree lidar is
used to map the environment with an obstacle. And by
using path planning algorithm robot chooses its own
path to reach some destination point by avoiding the
obstacle.
 
BLOCK DIAGRAM
 
PROJECT DESCRIPTION
 
Raspberry Pi is used with ROS software libraries
RPLidar A1 360 degree lidar interfaced with the Raspberry Pi publishes the Laser scan data,
which is received by subscribing the same ROS Topic in Matlab ROS Package.
Initially, mapping is done throughout the environment using Laser scan from Lidar.
If there is obstacle it gets also differentiated in the Laser scan map since before and after the
scan is plotted of obstacle presence.
Binary occupancy grid can be generated and prompts to choose the destination in the Map
By using PRM (Probabilibitic Road Map) algorithm, with the number of nodes and length of
connecting node distance path can be generated from the starting point to the destination
point with the avoidance of colliding walls.
Now the path following is performed to reach the destination.
 
HARDWARE USED
 
Raspberry Pi 3
SD Card 16 GB class 10
RPLidar A1
Robot Setup
Power Bank  (10000 mAh, 2 A minimum)
Arduino UNO
HC-05 Bluetooth Module
L293D Driver module
 
SOFTWARE USED
 
ROS kinetic OS image for Raspberry Pi
Matlab, which has a Robotic Operating System Software Package
Arduino IDE
SD Card Formatter
Etcher/win32Disk Imager/Rufus
 
RESULTS
 
Mapping
 
 
OCCUPANCY MAP
 
DESTINATION MARKING IN BINARY OCCUPANCY GRID
 
PATH PLANNING USING PRM
 (PROBABILISTIC ROAD MAP)
 
PATH PLANNING
 
THANK YOU
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Obstacle avoidance in robotics has evolved from basic collision avoidance to autonomous path planning with the use of Lidar and ROS. This project involves mapping the environment using Lidar scans and implementing a path planning algorithm in Matlab to navigate around obstacles. By utilizing a Raspberry Pi and ROS, the robot can choose alternative paths to reach its destination, making obstacle avoidance efficient and intelligent. The system offers a significant upgrade from conventional obstacle sensing methods, enhancing the robot's autonomy and decision-making capabilities.

  • Robotics
  • Path Planning
  • Lidar
  • Raspberry Pi
  • Matlab

Uploaded on Aug 03, 2024 | 2 Views


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  1. OBSTACLE AVOIDANCE ROBOT USING ROS & LIDAR WITH RASPBERRY PI, MATLAB OBSTACLE AVOIDANCE ON LONG DISTANCE WITH PATH PLANNING

  2. INTRODUCTION Obstacle avoiding methods are used from least to the ultimate models. It is used to avoid the collision on obstacles. But before in old methods, there is no autonomous option to choose the alternative path when the obstacle is present in the way. But this can be possible now by using LIDAR with ROS, by using LIDAR scans mapping is done. So that the Bot knows the complete map of the environment and by using PRM for Path planning algorithm in Matlab alternative path can be chosen.

  3. ABOUT MATLAB ROS In the Latest version of Matlab, it has ROS (Robotic Operating System) software supporting package. By using that its system can able to communicate with the ROS robot using ROS Network configurations.

  4. EXISTING SYSTEM In the existing obstacle avoidance robot, simply the sensors like IR and Ultrasonic sensors are used to sense the obstacle. It doesn t have a feature to choose the alternative path and to follow it.

  5. PROPOSED SYSTEM In this proposed system, by using 60-degree lidar is used to map the environment with an obstacle. And by using path planning algorithm robot chooses its own path to reach some destination point by avoiding the obstacle.

  6. BLOCK DIAGRAM

  7. PROJECT DESCRIPTION Raspberry Pi is used with ROS software libraries RPLidar A1 360 degree lidar interfaced with the Raspberry Pi publishes the Laser scan data, which is received by subscribing the same ROS Topic in Matlab ROS Package. Initially, mapping is done throughout the environment using Laser scan from Lidar. If there is obstacle it gets also differentiated in the Laser scan map since before and after the scan is plotted of obstacle presence. Binary occupancy grid can be generated and prompts to choose the destination in the Map By using PRM (Probabilibitic Road Map) algorithm, with the number of nodes and length of connecting node distance path can be generated from the starting point to the destination point with the avoidance of colliding walls. Now the path following is performed to reach the destination.

  8. HARDWARE USED Raspberry Pi 3 SD Card 16 GB class 10 RPLidar A1 Robot Setup Power Bank (10000 mAh, 2 A minimum) Arduino UNO HC-05 Bluetooth Module L293D Driver module

  9. SOFTWARE USED ROS kinetic OS image for Raspberry Pi Matlab, which has a Robotic Operating System Software Package Arduino IDE SD Card Formatter Etcher/win32Disk Imager/Rufus

  10. RESULTS Mapping

  11. OCCUPANCY MAP

  12. DESTINATION MARKING IN BINARY OCCUPANCY GRID

  13. PATH PLANNING USING PRM (PROBABILISTIC ROAD MAP)

  14. PATH PLANNING

  15. THANK YOU

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