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While multiple studies have proposed methods for the formation control of unmanned aerial vehicles (UAV), the trajectories generated are generally unsuitable for tracking targets where the optimum coverage of the target by the formation is required at all times. We propose a path planning approach called the Flux Guided (FG) method, which generates collision-free trajectories while maximising the coverage of one or more targets. We show that by reformulating an existing least-squares flux minimisation problem as a constrained optimisation problem, the paths obtained are $1.5 times$ shorter and track directly toward the target. Also, we demonstrate that the scale of the formation can be controlled during flight, and that this feature can be used to track multiple scattered targets. The method is highly scalable since the planning algorithm is only required for a sub-set of UAVs on the open boundary of the formations surface. Finally, through simulating a 3d dynamic particle system that tracks the desired trajectories using a PID controller, we show that the resulting trajectories after time-optimal parameterisation are suitable for robotic controls.
In this paper, we propose a joint indoor localization and navigation algorithm to enable a swarm of unmanned aerial vehicles (UAVs) to deploy in a specific spatial formation in indoor environments. In the envisioned scenario, we consider a static use
This work details the problem of aerial target capture using multiple UAVs. This problem is motivated from the challenge 1 of Mohammed Bin Zayed International Robotic Challenge 2020. The UAVs utilise visual feedback to autonomously detect target, app
This paper studies the collision avoidance problem for autonomous multiple fixedwing UAVs in the complex integrated airspace. By studying and combining the online path planning method, the distributed model predictive control algorithm, and the geome
The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque-driven control. The spiking cerebe
Differential Dynamic Programming (DDP) is an indirect method for trajectory optimization. Its efficiency derives from the exploitation of temporal structure (inherent to optimal control problems) and explicit roll-out/integration of the system dynami