RB5 Low-Cost Explorer: Implementing Autonomous Long-Term Exploration on Low-Cost Robotic Hardware
<|reference_start|>RB5 Low-Cost Explorer: Implementing Autonomous Long-Term Exploration on Low-Cost Robotic Hardware: This systems paper presents the implementation and design of RB5, a wheeled robot for autonomous long-term exploration with fewer and cheaper sensors. Requiring just an RGB-D camera and low-power computing hardware, the system consists of an experimental platform with rocker-bogie suspension. It operates in unknown and GPS-denied environments and on indoor and outdoor terrains. The exploration consists of a methodology that extends frontier- and sampling-based exploration with a path-following vector field and a state-of-the-art SLAM algorithm. The methodology allows the robot to explore its surroundings at lower update frequencies, enabling the use of lower-performing and lower-cost hardware while still retaining good autonomous performance. The approach further consists of a methodology to interact with a remotely located human operator based on an inexpensive long-range and low-power communication technology from the internet-of-things domain (i.e., LoRa) and a customized communication protocol. The results and the feasibility analysis show the possible applications and limitations of the approach.<|reference_end|>
@article{seewald2024rb5,
    title={RB5 Low-Cost Explorer: Implementing Autonomous Long-Term Exploration on
  Low-Cost Robotic Hardware},
    author={Adam Seewald, Marvin Chanc'an, Connor M. McCann, Seonghoon Noh, Omeed
  Fallahi, Hector Castillo, Ian Abraham, Aaron M. Dollar},
    journal={arXiv preprint arXiv:2402.08897},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.08897},
    primaryClass={cs.RO}
}