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Planning for Aerial Robot Teams for Wide-Area Biometric and Phenotypic Data Collection

Shashwata Mandal, Tianshuang Gao, Sourabh Bhattacharya

Year
2021
Citations
3

Abstract

This work presents an efficient and implementable solution to the problem of joint task allocation and path planning in a multi-UAV platform. The sensing requirement associated with the task gives rise to an uncanny variant of the traditional vehicle routing problem with coverage/sensing constraints. As is the case in several multi-robot path-planning problems, our problem reduces to an mTSP problem. In order to tame the computational challenges associated with the problem, we propose a hierarchical solution that decouples the vehicle routing problem from the target allocation problem. As a tangible solution to the allocation problem, we use a clustering-based technique that incorporates temporal uncertainty in the cardinality and position of the robots. Finally, we implement the proposed techniques on our multi-quadcopter platforms.

Keywords

Computer scienceMotion planningTask (project management)RobotRouting (electronic design automation)Vehicle routing problemQuadcopterCluster analysisArtificial intelligenceSonar

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