Source Seeking in Unknown Environments with Convex Obstacles
Source Seeking in Unknown Environments with Convex Obstacles
复制标题
在具有凸障碍的未知环境中寻找源
DOI：
10.23919/acc50511.2021.9483164
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
George Pappas
中科院分区：
文献类型：
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作者：
B. Angélico;Luiz F. O. Chamon;Santiago Paternain;Alejandro Ribeiro;George Pappas
导航任务通常不能根据目标来定义，要么是因为全球位置信息不可用或不可靠，要么是因为目标位置不是事先明确知道的。这个任务通常被间接地定义为一个源搜索问题，在这个问题中，自治智能体导航以最小化源诱导的凸势，同时避开障碍。这项工作解决了当只有位势的标量测量可用时的问题，即没有梯度信息。为此，它构造了一个人工势能，在这个势能上，精确的梯度动力学将在一个有凸起障碍物的世界中生成到目标的无碰撞轨迹。然后，利用极值搜索控制回路，最大限度地减少这种人工潜力，以平稳地导航到震源位置。我们证明了所提出的解决方案不仅找到了源头，而且还避开了任何障碍。用速度驱动粒子的数值结果、ROS+Gazebo全向机器人的仿真和机器人在环实验验证了该方法的有效性。
Navigation tasks often cannot be defined in terms of a target, either because global position information is unavailable or unreliable or because target location is not explicitly known a priori. This task is then often defined indirectly as a source seeking problem in which the autonomous agent navigates so as to minimize the convex potential induced by a source while avoiding obstacles. This work addresses this problem when only scalar measurements of the potential are available, i.e., without gradient information. To do so, it constructs an artificial potential over which an exact gradient dynamics would generate a collision-free trajectory to the target in a world with convex obstacles. Then, leveraging extremum seeking control loops, it minimizes this artificial potential to navigate smoothly to the source location. We prove that the proposed solution not only finds the source, but does so while avoiding any obstacle. Numerical results with velocity-actuated particles, simulations with an omni-directional robot in ROS+Gazebo, and a robot-in-the-loop experiment are used to illustrate the performance of this approach.