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.

翻译：本系统论文介绍了RB5的设计与实现，这是一种配备较少且成本更低的传感器、用于自主长期探索的轮式机器人。该系统仅需RGB-D相机和低功耗计算硬件，采用配备摇臂转向架悬架的实验平台。它可在未知且无GPS的环境中运行，并适应室内外地形。探索方法包含一种将前沿与基于采样的探索技术相结合的方法，并配备路径跟踪向量场和先进SLAM算法。该方法使机器人能以较低的更新频率探索周围环境，从而在保持良好自主性能的同时，允许使用性能较低、成本更低的硬件。此外，该方法还包含基于物联网领域的低成本、低功耗远距离通信技术（即LoRa）及定制通信协议，与远程人类操作员进行交互的方案。实验结果与可行性分析展示了该方法的潜在应用场景及其局限性。