Singh Chahat Deep, He Botao, Fermüller Cornelia, Metzler Christopher, Aloimonos Yiannis
Perception and Robotics Group, Department of Computer Science, University of Maryland, College Park, MD, United States.
Perception, Robotics, AI and Sensing (PRAISe) Lab, Department of Mechanical Engineering, University of Colorado, Boulder, CO, United States.
Front Robot AI. 2024 Sep 18;11:1431826. doi: 10.3389/frobt.2024.1431826. eCollection 2024.
The rapidly increasing capabilities of autonomous mobile robots promise to make them ubiquitous in the coming decade. These robots will continue to enhance efficiency and safety in novel applications such as disaster management, environmental monitoring, bridge inspection, and agricultural inspection. To operate autonomously without constant human intervention, even in remote or hazardous areas, robots must sense, process, and interpret environmental data using only onboard sensing and computation. This capability is made possible by advancements in perception algorithms, allowing these robots to rely primarily on their perception capabilities for navigation tasks. However, tiny robot autonomy is hindered mainly by sensors, memory, and computing due to size, area, weight, and power constraints. The bottleneck in these robots lies in the real-time perception in resource-constrained robots. To enable autonomy in robots of sizes that are less than 100 mm in body length, we draw inspiration from tiny organisms such as insects and hummingbirds, known for their sophisticated perception, navigation, and survival abilities despite their minimal sensor and neural system. This work aims to provide insights into designing a compact and efficient minimal perception framework for tiny autonomous robots from higher cognitive to lower sensor levels.
自主移动机器人能力的迅速提升有望在未来十年使其无处不在。这些机器人将继续在诸如灾害管理、环境监测、桥梁检测和农业检测等新应用中提高效率和安全性。为了在没有持续人工干预的情况下自主运行，即使是在偏远或危险区域，机器人必须仅使用机载传感和计算来感知、处理和解释环境数据。感知算法的进步使这种能力成为可能，使这些机器人在导航任务中主要依赖其感知能力。然而，由于尺寸、面积、重量和功率限制，微型机器人的自主性主要受到传感器、内存和计算能力的阻碍。这些机器人的瓶颈在于资源受限机器人的实时感知。为了实现体长小于100毫米的机器人的自主性，我们从昆虫和蜂鸟等微小生物身上汲取灵感，它们以其复杂的感知、导航和生存能力而闻名，尽管它们的传感器和神经系统极为简单。这项工作旨在为从高级认知到低级传感器层面的微型自主机器人设计一个紧凑且高效的最小感知框架提供见解。
