用群体数量简单导航未知环境,无需复杂感知或通信。
Power in Numbers: Primitive Algorithm for Swarm Robot Navigation in Unknown Environments
- 仅依赖目标方向和邻近机器人位置,实现群体导航。
- 数学验证+仿真+实机实验均证明算法有效。
- 适合资源受限的微型机器人集群,如灾害搜救。
近年来,移动机器人在未知环境中的导航成为重要研究方向。以往方法多依赖摄像头、激光雷达实时建图,结合自定位与路径规划,或通过模拟到现实的迁移学习让机器人在真实场景中应用预训练策略。然而,对动态变化的未知环境进行高精度感知与建模仍极为复杂。本文提出一种基于群体机器人数目的简单导航算法:机器人仅需感知目标方向及周围同伴相对位置,即可通过持续朝向目标并绕开其他机器人完成导航。该方法无需环境感知、无需判断是否被困、也无需复杂的机器人间通信。论文从数学上验证了算法有效性,并基于势场法开展数值仿真,最后通过基于声场导航的自主开发机器人进行实验验证。
原文摘要 · Abstract (English)
Recently, the navigation of mobile robots in unknown environments has become a particularly significant research topic. Previous studies have primarily employed real-time environmental mapping using cameras and LiDAR, along with self-localization and path generation based on those maps. Additionally, there is research on Sim-to-Real transfer, where robots acquire behaviors through pre-trained reinforcement learning and apply these learned actions in real-world navigation. However, strictly the observe action and modelling of unknown environments that change unpredictably over time with accuracy and precision is an extremely complex endeavor. This study proposes a simple navigation algorithm for traversing unknown environments by utilizes the number of swarm robots. The proposed algorithm assumes that the robot has only the simple function of sensing the direction of the goal and the relative positions of the surrounding robots. The robots can navigate an unknown environment by simply continuing towards the goal while bypassing surrounding robots. The method does not need to sense the environment, determine whether they or other robots are stuck, or do the complicated inter-robot communication. We mathematically validate the proposed navigation algorithm, present numerical simulations based on the potential field method, and conduct experimental demonstrations using developed robots based on the sound fields for navigation.
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