Adapting Low-Cost Platforms for Robotics Research
This work addresses practical challenges in robotics research for researchers using low-cost platforms, but it is incremental as it builds on existing adaptation efforts.
The paper discusses adapting the low-cost, open-source EvoBot platform for robotics research, highlighting common failures and practical limitations in tasks like localization and path planning, and proposes generalized solutions.
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.