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In this paper, we present a decentralized cooperative multiple target tracking method for multiple Unmanned Aerial Vehicles (UAVs). The decentralized cooperative multi-target tracking algorithm incorporates an optimal sensor management scheme and a cooperative path planner. To localize and track targets, a set of Extended Kalman Filters (EKFs) is used onboard each UAV and resulting target estimates...
In this paper, we study the distributed optimal flocking control problem of multiple Unmanned Aircraft Systems (Multi-UAS). Using the emerging Neuro Dynamic Programming (NDP) technique, a novel distributed near optimal flocking design is proposed for ensuring the multi-UAS to follow the three heuristic flocking rules (i.e. cohesion, separation and alignment) in an optimal manner. First, an innovative...
This paper discusses the control strategies of a fleet of robots, especially the control by the virtual leader. The main contribution consists is to achieve the control of a group of vehicles while following a predefined mission carried out thanks to a virtual leader, and simultaneously avoiding the collisions between the different agents of the group. The approach proposed in this paper is based...
This paper presents a method to generate and follow a smallest weighted path in 3D by quadcopter. A smallest weighted path is obtained using Dijkstra's algorithm based on terrain information. To follow the generated path we use a Model predictive control that takes constraints on jerks, position and angular acceleration on the quadcopter. Simulation results are presented to validate our approach.
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