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See detailSafer UAV Piloting: A Robust Sense-and-Avoid Solution for Remotely Piloted Quadrotor UAVs in Complex Environments
Wang, Min UL; Voos, Holger UL

in Safer UAV Piloting: A Robust Sense-and-Avoid Solution for Remotely Piloted Quadrotor UAVs in Complex Environments (2019, December)

Current commercial UAVs are to a large extent remotely piloted by amateur human pilots. Due to lack of teleoperation experience or skills, they often drive the UAVs into collision. Therefore, in order to ... [more ▼]

Current commercial UAVs are to a large extent remotely piloted by amateur human pilots. Due to lack of teleoperation experience or skills, they often drive the UAVs into collision. Therefore, in order to ensure safety of the UAV as well as its surroundings, it is necessary for the UAV to boast the capability of detecting emergency situation and acting on its own when facing imminent threat. However, the majority of UAVs currently available in the market are not equipped with such capability. To fill in the gap, in this paper we present a complete sense-and-avoid solution for assisting unskilled pilots in ensuring a safe flight. Particularly, we propose a novel nonlinear vehicle control system which takes into account of sensor characteristics, an emergency evaluation policy and a novel optimization-based avoidance control strategy. The effectiveness of the proposed approach is demonstrated and validated in simulation with multiple moving objects. [less ▲]

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See detailRobust Online Obstacle Detection and Tracking for Collision-free Navigation of Multirotor UAVs in Complex Environments
Wang, Min UL; Voos, Holger UL; Su, Daobilige

in 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore 18-21 November 2018 (2018)

Object detection and tracking is a challenging task, especially for unmanned aerial robots in complex environments where both static and dynamic objects are present. It is, however, essential for ensuring ... [more ▼]

Object detection and tracking is a challenging task, especially for unmanned aerial robots in complex environments where both static and dynamic objects are present. It is, however, essential for ensuring safety of the robot during navigation in such environments. In this work we present a practical online approach which is based on a 2D LIDAR. Unlike common approaches in the literature of modeling the environment as 2D or 3D occupancy grids, our approach offers a fast and robust method to represent the objects in the environment in a compact form, which is significantly more efficient in terms of both memory and computation in comparison with the former. Our approach is also capable of classifying objects into categories such as static and dynamic, and tracking dynamic objects as well as estimating their velocities with reasonable accuracy. [less ▲]

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