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Active autonomous aerial exploration for ground robot path planning

机译:主动自主空中探索,用于地面机器人路径规划

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摘要

We address the problem of planning a path for a ground robot through unknown terrain, using observations from a flying robot. In search and rescue missions, which are our target scenarios, the time from arrival at the disaster site to the delivery of aid is critically important. Previous works required exhaustive exploration before path planning, which is time-consuming but eventually leads to an optimal path for the ground robot. Instead, we propose active exploration of the environment, where the flying robot chooses regions to map in a way that optimizes the overall response time of the system, which is the combined time for the air and ground robots to execute their missions. In our approach, we estimate terrain classes throughout our terrain map, and we also add elevation information in areas where the active exploration algorithm has chosen to perform 3-D reconstruction. This terrain information is used to estimate feasible and efficient paths for the ground robot. By exploring the environment actively, we achieve superior response times compared to both exhaustive and greedy exploration strategies. We demonstrate the performance and capabilities of the proposed system in simulated and real-world outdoor experiments. To the best of our knowledge, this is the first work to address ground robot path planning using active aerial exploration.
机译:我们使用飞行机器人的观测结果来解决规划地面机器人穿越未知地形的路径的问题。在搜索和救援任务(这是我们的目标方案)中,从到达灾难现场到提供援助的时间至关重要。以前的工作需要在路径规划之前进行详尽的探索,这很耗时,但最终会为地面机器人带来最佳路径。取而代之的是,我们建议积极探索环境,在这种环境中,飞行机器人选择区域的方式可以优化系统的整体响应时间,这是空中和地面机器人执行任务的总时间。在我们的方法中,我们估算整个地形图的地形类别,并在主动勘探算法已选择执行3-D重建的区域中添加海拔信息。该地形信息用于估算地面机器人的可行和有效路径。通过积极地探索环境,与穷举和贪婪的探索策略相比,我们可以实现更好的响应时间。我们在模拟和真实世界的户外实验中演示了所提出系统的性能和功能。据我们所知,这是使用主动空中探测解决地面机器人路径规划的第一项工作。

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