ABSTRACT
The path planning of a mobile robot in this paper is a result of a recent work based on
previous use of LIDAR sensors. Lidar sensors have been in use for many years now in
various fields for numerous purposes. Path planning, environment mapping, obstacle
avoidance, weather mapping, terrain mapping and etc. have been the major
application of a Lidar sensor.
The work in this thesis consists of the use of RPLIDAR A1 sensor from Robo Peak for
the development of the algorithm for environment mapping, localization and
trajectory planning with obstacle avoidance in indoor environment.
At first it is about learning the limitations and calibrating the sensor for optimal use in
closed environment. This is followed by the development of algorithm for mapping the
said environment. Then the second stage of development requires us to develop
algorithm for trajectory planning and localization or SLAM.
The central part of the work consists of the development of efficient and productive
algorithm for mapping and path planning in a simulated environment.
Finally it produces the possibility of reading of the local environment and trajectory
planning in closed environment. This information can be useful in developing in-house
robots for service industry that can be used in restaurants, offices and house and be a
part of our daily lives while making them easier and more productive. Use of 3D
sensors and cameras can vastly improve the performance and usability of the mobile
robot.
Table of Contents
Abstract
1
Index 7
List of symbols 9
1 Introduction 10
11 Introduction of mobile robotics 10
12 Introduction of LIDAR sensors 13
2 State of ART 15
21 Types of Sensors 15
22 Types of Algorithm 16
23 Path Planning Approach 18
3 RPLIDAR A1 19
31 Introduction to RPLIDAR A1 19
311 System Connection 20
312 Mechanism 20
313 Safety and Scope 21
314 Data Output 21
315 Application Scenarios 22
4 Experimental Test 23
41 Calibration of RPLIDAR A1 23
a Graphs 24
b MATLAB Plot 25
42 Calibration Test 2 of RPLIDAR A1 26
a Graphs 27
43 Results 27
5 Environment Mapping 28
51 SLAM Mapping 28
52 Environmental Setup 28
53 MATLAB Code 29
54 Frame Transformations 30
55 SLAM Level Operations 32
56 EKF-SLAM Code 34
6 Conclusion 40
7 Appendix 41
8 Bibliography 42
9 List of Figures and Tables 43
