Online world modeling and path planning for an unmanned helicopter

  • Authors:

  • Franz Andert;Florian Adolf

  • Affiliations:

  • German Aerospace Center (DLR), Institute of Flight Systems, Braunschweig, Germany 38108;German Aerospace Center (DLR), Institute of Flight Systems, Braunschweig, Germany 38108

  • Venue:
  • Autonomous Robots
  • Year:
  • 2009

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Abstract

Mission scenarios beyond line of sight or with limited ground control station access require capabilities for autonomous safe navigation and necessitate a continuous extension of existing and potentially outdated information about obstacles. The presented approach is a novel synthesis of techniques for 3D environment perception and global path planning. A locally bounded sensor fusion approach is used to extract sparse obstacles for global incremental path planning in an anytime fashion. During the flight, a stereo camera checks the field of view along the flight path ahead by analyzing depth images. A 3D occupancy grid is built incrementally. To reduce the high data rate and storage demands of grid-type maps, an approximated polygonal world model is created. For a compacted representation, it uses prisms and ground planes. This enables the system to constantly renew and update its knowledge about obstacles. An incremental heuristic path planner uses both a-priori information as well as incremental obstacle updates to assure a collision-free path at any time. Mapping results from flight tests show the functionality of onboard world modeling from real sensor data. Path planning feasibility is demonstrated within a simulation environment considering world model changes inside the vehicle's field of view.