Journal of Aerospace System Engineering (항공우주시스템공학회지)

The Society for Aerospace System Engineering (항공우주시스템공학회)
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Obstacle Avoidance for Unmanned Air Vehicles Using Monocular-SLAM with Chain-Based Path Planning in GPS Denied Environments

  • Bharadwaja, Yathirajam (Academy of Scientific and Innovative Research (AcSIR), Aerospace Electronics and Systems Division, CSIR-National Aerospace Laboratories) ;
  • Vaitheeswaran, S.M (Academy of Scientific and Innovative Research (AcSIR), Aerospace Electronics and Systems Division, CSIR-National Aerospace Laboratories) ;
  • Ananda, C.M (Academy of Scientific and Innovative Research (AcSIR), Aerospace Electronics and Systems Division, CSIR-National Aerospace Laboratories)
  • Received : 2018.10.13
  • Accepted : 2020.04.10
  • Published : 2020.04.30
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Abstract

Detecting obstacles and generating a suitable path to avoid obstacles in real time is a prime mission requirement for UAVs. In areas, close to buildings and people, detecting obstacles in the path and estimating its own position (egomotion) in GPS degraded/denied environments are usually addressed with vision-based Simultaneous Localization and Mapping (SLAM) techniques. This presents possibilities and challenges for the feasible path generation with constraints of vehicle dynamics in the configuration space. In this paper, a near real-time feasible path is shown to be generated in the ORB-SLAM framework using a chain-based path planning approach in a force field with dynamic constraints on path length and minimum turn radius. The chain-based path plan approach generates a set of nodes which moves in a force field that permits modifications of path rapidly in real time as the reward function changes. This is different from the usual approach of generating potentials in the entire search space around UAV, instead a set of connected waypoints in a simulated chain. The popular ORB-SLAM, suited for real time approach is used for building the map of the environment and UAV position and the UAV path is then generated continuously in the shortest time to navigate to the goal position. The principal contribution are (a) Chain-based path planning approach with built in obstacle avoidance in conjunction with ORB-SLAM for the first time, (b) Generation of path with minimum overheads and (c) Implementation in near real time.

Keywords

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