Adapting Low-Cost Platforms for Robotics Research

TL;DR

This paper explores the adaptation of the low-cost EvoBot platform for diverse robotics research tasks, highlighting practical challenges, lessons learned, and potential solutions to facilitate real-world algorithm validation.

Contribution

It provides insights into the practical limitations of low-cost robotics platforms and offers generalizable solutions for researchers adapting such platforms for various robotics applications.

Findings

Identification of common failures in low-cost platform adaptation

Demonstration of tasks like localization, control, swarm consensus, and path planning

Proposed solutions to practical challenges encountered

Abstract

Validation of robotics theory on real-world hardware platforms is important to prove the practical feasibility of algorithms. This paper discusses some of the lessons learned while adapting the EvoBot, a low-cost robotics platform that we designed and prototyped, for research in diverse areas in robotics. The EvoBot platform was designed to be a low cost, open source, general purpose robotics platform intended to enable testing and validation of algorithms from a wide variety of sub-fields of robotics. Throughout the paper, we outline and discuss some common failures, practical limitations and inconsistencies between theory and practice that one may encounter while adapting such low-cost platforms for robotics research. We demonstrate these aspects through four representative common robotics tasks- localization, real-time control, swarm consensus and path planning applications, performed using the EvoBots. We also propose some potential solutions to the encountered problems and try to generalize them.