Abstract
In this paper, we study the problem of conflict detection and resolution for unmanned aerial vehicle (UAV) swarms. Specially, we propose a distributed conflict detection and resolution method for multi-UAVs in formation based on consensus algorithm and strategy coordination. When encountering threat swarms, the UAVs in one swarm act as one unit and are together treated as one control object. Each swarm in conflict selects three candidate collision avoidance maneuvers from the preset strategy pool, generates the corresponding planned trajectories with an uncertainty trajectory modeling, and then broadcasts and shares them. All of the swarms in conflict coordinate and determine an optimal combination of strategies. When a collision is imminent, the primary strategy is activated. Each swarm adopts a “leader-follower” strategy, where the leader UAV is regarded as the controller and flies independently, and the others follow the leader UAV. During motion, a decentralized consensus algorithm is adopted for agents to converge to their positions for the desired formation and to maintain a stable geometric configuration. A temporal and spatially integrated conflict-detection model is improved, especially for UAV swarms. A token-allocation strategy is especially improved for distributed coordination to resolve the partial knowledge of the airspace condition. Damping of the coordination is proposed to address data dropouts and transmission delays. Two typical scenarios are conducted to test the methodology proposed in this paper. The simulation result demonstrates the effectiveness and rationality of the proposed methodology.
Highlights
In recent years, clustering and autonomy have gradually become one of the major trends of development for unmanned aerial vehicles (UAVs)
Conflict-detection and resolution (CDR) algorithms play a critical role in guaranteeing the flight safety of UAVs
This paper proposes a distributed conflict detection and resolution (CDR) method for multi-UAVs in formation based on consensus algorithm and strategy coordination
Summary
In recent years, clustering and autonomy have gradually become one of the major trends of development for unmanned aerial vehicles (UAVs). This paper proposes a distributed conflict detection and resolution (CDR) method for multi-UAVs in formation based on consensus algorithm and strategy coordination. Most control algorithms with CDR only concentrate on collision avoidance among agents in a swarm and guarantee the order and security of a formation, but they rarely consider external dynamic threats such as other invading UAV formations. The former mainly includes geometric collision avoidance algorithms (GA) which analyze relative spatial geometric relations between pair UAVs and provide a passive CA strategy The latter mainly contains trajectory-planning algorithms (TPA) which actively plan conflict-free routes connecting different locations. A. MODELING A NETWORK STRUCTURE OF A SWARM In this paper, an asymmetric formation control is adopted [27] where, for each distance-keeping task in the corresponding agent pair, only one aircraft is responsible. The problem is approached by a two-level control scheme: At the high level, a trajectory generator is designed for leader aircraft; At the low level, individual motion controller is designed for follower aircraft to track the trajectories generated at high level [2]
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