Robust Real-time Sense-and-Avoid Solutions for Remotely Piloted Quadrotor UAVs in Complex Environments

UAV teleoperation is a demanding task: to successfully accomplish the mission without collision requires skills and experience. In real-life environments, 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 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 work we present 2D LIDAR based Sense-and-Avoid solutions which are able to actively assist unskilled human operator in obstacle avoidance, so that the operator can focus on high-level decisions and global objectives in UAV applications such as search and rescue, farming etc. Specifically, with our novel 2D LIDAR based obstacle detection and tracking algorithm, perception-assistive flight control design, progressive emergency evaluation policies and optimization based and adaptive virtual cushion force field (AVCFF) based avoidance strategies, our proposed UAV teleoperation assistance systems are capable of obstacle detection and tracking, as well as automatic obstacle avoidance in complex environment where both static and dynamic objects are present. Additionally, while the optimization based solution is validated in Matlab, the AVCFF based avoidance system has been fully integrated with sensing system, perception-assistive flight controller on the basis of the Hector Quadrotor open source framework, and the effectiveness of the complete Sense-and-Avoid solution has been demonstrated and validated on a realistic simulated UAV platform in Gazebo simulations, where the UAV is operated at a high speed.