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Assisted teleoperation of quadcopters using obstacle avoidance

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Języki publikacji
EN
Abstrakty
EN
Teleoperation of unmanned aerial vehicles often demands extensive training. Yet, even well trained pilots are prone to mistakes, resulting frequently in collisions of the vehicle with obstacles. This paper presents a method to assist the tele-operation of a quadrotor using an obstacle avoidance approach. In particular, rough map of the nearby environment is constructed using sonar sensors. This map is constructed using FastSLAM to allow tracking of the vehicle position with respect to the map. The map is then used to override operator commands that may lead to a collision. An unknown and GPS denied environment is considered. Experimental results using the USARsim simulator are presented.
Twórcy
autor
  • Institute for Systems and Robotics, Instituto Superior Técnico, Portugal
autor
  • Institute for Systems and Robotics, Instituto Superior Técnico, Portugal
Bibliografia
  • [1] S. Bouabdallah, “Design and Control of an Indoor Micro Quadrotor”. In: Proceedings of International Conference on Robotics and Automation, 2004.
  • [2] A. Stentz, D. Fox and M. Montemerlo, “FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem with Unknown Data Association”. In: Proceedings of the AAAI National Conference on Artificial Intelligence, 2003.
  • [3] A. Elfes, “Occupancy grids: A probabilistic framework for robot perception and navigation”, Ph.D.dissertation, Carnegie Mellon University, 1989.
  • [4] C. Stachniss, D. Hähnell,W. Burgard, G. Grisetti, “On Actively Closing Loops in Grid-based FastSLAM”, Advanced Robotics, vol. 19, 2005.
  • [5] M. Montemerlo, S. Thrun, D. Koller, B. Wegbreit, “FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem”. In: Proceedings of the AAAI National Conference on Artificial Intelligence, 2002, pp. 593-598.
  • [6] Z. He, R. Iyer, P. Chandler, “Vision-Based UAV Flight Control and Obstacle Avoidance”. In: Proceedings of the American Control Conference, 2006, pp. 2166-2170.
  • [7] S. Thrun,W. Burgard, D. Fox, “Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)”, The MIT Press, 2005.
  • [8] N. Gordon, D. Salmond, A. Smith, “Radar and Signal Processing”, IEEE Proceedings, vol. 140, 1993,pp. 107-113.
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Bibliografia
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