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Event Details

  • Tuesday, November 7, 2017
  • 11:00 - 11:30

Planning Algorithm and Multi-Vehicle Formation for Environmental Monitoring by Using Low-Cost UAVs

Environmental monitoring using autonomous low-cost Unmanned Ariel Vehicles (UAVs) have been emerged as an efficient and unique robotic application. Inspecting large terrains (e.g. natural reservers, water reservoirs ) is considered an intensive task for humans and critical by its nature since missing any detail could affect nature ecosystems and its integrity. Furthermore, natural environments inspection is a time and resource intensive task that should be performed as eciently and accurately as possible. In this talk, it is proposed a coverage planning algorithm for inspecting large terrais that maybe include complex natural structures, using low-cost UAVs. The proposed method follows a model based coverage path planning approach which generates an optimized path that passes through a set of admissible waypoints sampled uniformly to cover a relative complex environments. The algorithm provides a prediction of the relative coverage of the regions by using “a priori” representations or maps. A search space coverage path planner technique is proposed that uses UAV's on-board sensors' models to generate optimal paths that maximize coverage and accuracy and minimize travelled distance. In addition, a pattern formation for use of multi-uav systems is proposed to achieve geometric patterns and overlook the visibility limitation in UAVs. A methodology to reach a complete coordinate agreement is adopted to achieve a desired pattern. In this talk, a decentralized approach for circle formation is highlighted. Simulation results have validated the robustness of the proposed algorithm, where the pattern has been successfully constructed in a self-organized manner an UAV swarm.