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Persistent Monitoring with Refueling on a Terrain Using a Team of Aerial and Ground Robots

Parikshit Maini, Kevin Yu, P. B. Sujit, Pratap Tokekar

发表年份
2018
引用次数
35

摘要

There are many applications such as surveillance and mapping that require persistent monitoring of terrains. In this work, we consider a heterogeneous team of aerial and ground robots that are tasked with monitoring a terrain along a given path. Both types of robots are equipped with cameras that can monitor the terrain within their fields-of-view. We also consider the ability of the aerial robots to land occasionally on the terrain to recharge. The objective is to find a path for all the robots to reduce the time required. Determining optimal routes for the robots is a challenging problem because of constrained visibility due to the terrain and fuel limitations of the robots. We devise an MILP formulation for the problem using a 1.5 dimensional representation model. A branch-and-cut framework is used to implement the MILP and involves the design of a separation algorithm to compute valid inequalities. We report results from extensive simulations and proof-of-concept field experiments to show the efficacy of our approach.

关键词

TerrainRobotComputer scienceVisibilitySearch and rescueRepresentation (politics)Motion planningField (mathematics)Artificial intelligenceReal-time computing

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