Laser Ranging Based Intelligent System for Unknown Environment Mapping

TL;DR

This paper presents an efficient laser-based navigation system for autonomous mapping in unknown environments, utilizing laser range data, particle filtering, and real-time processing on embedded hardware.

Contribution

It introduces a novel, computationally efficient INS that integrates laser data processing, obstacle avoidance, and localization for autonomous mapping.

Findings

Accurately maps unknown environments in real-time

Operates efficiently on embedded Raspberry Pi hardware

Demonstrates robustness in real-world tests

Abstract

This work describes the implementation of a simple and computationally efficient Intelligent Navigation System (INS) for autonomous systems used in areas where human access is impossible. The system uses Laser Range Finder (LRF) readings as input, making it suitable for mobile platform implementation. The INS pre-processes the LRF readings to remove noise and determines an obstacle-free path for mapping. The system's localization method uses a similarity transform and particle filter. The system was tested in artificially generated environments and emulated in real-time with real-environment data. The system was then implemented in a Raspberry Pi3 on a 3WD Omni-directional mobile platform and tested in real environments. The system was able to generate an accurate 2D map of the area. The proposed methodology was shown to be efficient through a comparative analysis of execution time.