Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Identifying Contingency Requirements Using Obstacle Analysis
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
Controlled observations of the genetic algorithm in a changing environment: case studies using the shaky ladder hyperplane-defined functions
Path planning algorithm for VTOL type UAVs based on the methods of ray tracing and limit cycle
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
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The integration of Unmanned Aerial Vehicles (UAVs) in airspace requires new methods to certify collision avoidance systems. This paper presents a safety clearance process for obstacle avoidance systems, where worst case analysis is performed using simulation based optimization in the presence of all possible parameter variations. The clearance criterion for the UAV obstacle avoidance system is defined as the minimum distance from the aircraft to the obstacle during the collision avoidance maneuver. Local and global optimization based verification processes are developed to automatically search the worst combinations of the parameters and the worst-case distance between the UAV and an obstacle under all possible variations and uncertainties. Based on a 6 Degree of Freedom (6DoF) kinematic and dynamic model of a UAV, the path planning and collision avoidance algorithms are developed in 3D space. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is a simple and widely used method. Different optimization algorithms are applied and compared in terms of the reliability and efficiency.