Abstract
An unmanned aerial vehicle (UAV) must be able to safely reach its destination even, when it can only gather limited information about its environment. When an obstacle is detected, the UAV must be able to choose a path that will avoid collision with the obstacle. For the collision avoidance scheme, we apply the velocity obstacle approach since it is applicable even with the UAV’s limited sensing capability. To be able to apply the velocity obstacle approach, we need to know the parameter values of the obstacle such as its size, current velocity and current position. However, due to the UAV’s limited sensing capability, such information about the obstacle is not available. Thus, by evaluating sensor readings, we get the changes in the possible positions of the obstacle in order to generate the velocity obstacle and make the UAV choose a collision-free trajectory towards the destination. We performed simulation on different obstacle movements and the collision-free trajectory of the UAV is shown in the simulation results.
Highlights
Many studies have focused on the full automation of low-cost unmanned aerial vehicles (UAVs)
Since Scenarios 4 and 5 have different initial position of the obstacle, it resulted to different sensor readings, generated different VOA|B and provided different choices of the velocities to be taken by the UAV
Since Scenarios 4 and 5 have different initial position of the obstacle, it resulted to different sensor readings, generated different | and provided different choices of the velocities to be taken by the UAV
Summary
Many studies have focused on the full automation of low-cost unmanned aerial vehicles (UAVs). Our work is based on the simple modeling of low-cost micro UAV with limited sensing capability. It does not model the dynamics of the system and does not take into account the noisy environment in sensing the obstacle. We apply the velocity obstacle approach introduced in [18] to be able to determine the possible maneuvers that the UAV can take to avoid collision. Reciprocal collision avoidance considers the navigation of many agents and in which each agent applies the velocity obstacle approach. We show how to overcome the UAV’s limited sensing capability to be able to find a collision-free trajectory to the goal with the use of the velocity obstacle approach.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
