7 accepted papers
We present a heuristic-guided multi-robot motion planning framework that solves the problem of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> dynamical agents visiting <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://
The dynamics of all real quadrotors inevitably differ even if they are the same product. In particular, the dynamics can change significantly during the flight due to additional device attachments or overheating motors. In this study, we focus on training a low-level controller, which operates in re…
We present a novel distributed robotic swarm algorithm inspired by the open channel siphon phenomenon displayed in certain viscoelastic fluids. Self-siphoning viscoelastic fluids are often able to mitigate the trapping effects of local minima in the environment. Using a similar strategy, our algorit
We compare the performance of five state of the art decentralized task allocation algorithms under imperfect communication conditions. The decentralized algorithms we consider are CBAA, ACBBA, DHBA, HIPC and PI. All algorithms are evaluated using three different models of communication, including th
In this letter, we address the problem of collision avoidance for a swarm of UAVs used for continuous surveillance of an urban environment. Our method, LSwarm, efficiently avoids collisions with static obstacles, dynamic obstacles and other agents in three-dimensional urban environments while consid
Motion planning for multi-target autonomous search requires efficiently gathering as much information over an area as possible with an imperfect sensor. In disaster scenarios and contested environments the spatial connectivity may unexpectedly change (due to aftershock, avalanche, flood, building co…
We consider the problem of real-time path-planning in a spatiotemporally varying wind-field with moving obstacles. We are provided with changing wind and obstacle predictions along a (D + 1)-dimensional space-time lattice. We present an Any-Time algorithm that quickly finds an αβ-suboptimal solution