[Paper Review] Real-World Modeling of a Pathfinding Robot Using Robot Operating System (ROS)

Sayyed Jaffar Ali Raza, Nitish A. Gupta+2 more|arXiv (Cornell University)|Feb 27, 2018

Robotic Path Planning Algorithms4 references3 citations

TL;DR

This paper presents a robust, reusable framework for implementing pathfinding algorithms on low-cost, real-world robotics platforms using ROS, addressing hardware-specific challenges such as wheel slippage, asynchronous motor control, odometry drift, and noisy sensor data. The authors demonstrate that with careful calibration and abstraction layers, standard algorithms like A* and Wavefront can be effectively deployed on non-ideal physical systems without simulation-only assumptions.

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.

Motivation & Objective

• To bridge the gap between simulation-based pathfinding and real-world robotic deployment on low-cost, non-commercial hardware.
• To address persistent real-world challenges such as wheel slippage, asynchronous motor behavior, and odometry drift in path planning systems.
• To develop a reusable, hardware-abstraction-friendly framework using ROS that enhances algorithm robustness across diverse physical platforms.
• To validate that standard pathfinding algorithms (e.g., A*, Wavefront) can function reliably in real-world conditions when combined with proper hardware-level compensation techniques.

Proposed method

• The authors implement a modular ROS-based architecture to decouple path planning logic from low-level hardware control.
• They apply sensor fusion techniques to mitigate abnormal sensory feedback and improve localization accuracy.
• Odometry correction is achieved through iterative calibration and feedback loops to reduce drift caused by wheel slippage.
• Asynchronous motor control is managed via PID-based velocity regulation to ensure consistent robot motion.
• The system uses a generic hardware abstraction layer to maintain portability across different robot platforms.
• Path planning algorithms (A*, Wavefront) are integrated into the ROS framework with real-time execution and dynamic obstacle avoidance.

Experimental results

Research questions

• RQ1 How can pathfinding algorithms be made robust to real-world hardware imperfections such as wheel slippage and motor inconsistency?
• RQ2 What architectural patterns in ROS enable reliable deployment of path planning on low-cost, non-commercial robotic platforms?
• RQ3 To what extent can sensor noise and odometry drift be compensated for using software-level calibration and feedback mechanisms?
• RQ4 Can standard pathfinding algorithms like A* and Wavefront be effectively deployed in real-world environments without simulation-only assumptions?
• RQ5 How can a reusable, hardware-agnostic framework be designed for path planning in real-world robotics?

Key findings

• The proposed framework successfully mitigates odometry drift through iterative calibration and feedback control, improving localization stability.
• Sensor noise and abnormal data were significantly reduced using software-level filtering and fusion techniques, enhancing path planning reliability.
• Asynchronous motors were stabilized using PID-based velocity control, enabling consistent robot motion during path execution.
• The A* and Wavefront algorithms achieved functional path planning in real-world environments despite hardware imperfections.
• The system demonstrated portability across different hardware platforms due to its abstraction layer, confirming reusability for future research.
• Real-world deployment revealed that simulation-only testing often overlooks critical dynamic issues such as wheel slippage and power instability, which were addressed in the implementation.