Real-World Modeling of a Pathfinding Robot Using Robot Operating System (ROS)

TL;DR

This paper discusses implementing robust pathfinding algorithms on real-world, low-cost robots using ROS, addressing practical issues like wheel slips, sensor anomalies, and hardware variability to improve reliability.

Contribution

It introduces design techniques for robust path planning algorithms that are adaptable across various hardware platforms, considering real-world challenges often overlooked in simulations.

Findings

Developed methods to handle wheel slip and odometry errors.

Implemented robust algorithms resilient to sensor anomalies.

Provided a general framework for real-world robot path planning.

Abstract

This paper presents a practical approach towards implementing pathfinding algorithms on real-world and low-cost non- commercial hardware platforms. While using robotics simulation platforms as a test-bed for our algorithms we easily overlook real- world exogenous problems that are developed by external factors. Such problems involve robot wheel slips, asynchronous motors, abnormal sensory data or unstable power sources. The real-world dynamics tend to be very painful even for executing simple algorithms like a Wavefront planner or A-star search. This paper addresses designing techniques that tend to be robust as well as reusable for any hardware platforms; covering problems like controlling asynchronous drives, odometry offset issues and handling abnormal sensory feedback. The algorithm implementation medium and hardware design tools have been kept general in order to present our work as a serving platform for future researchers and robotics enthusiast working in the field of path planning robotics.