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About this paper
Simon Idoko, Prajyot Jadhav, Arun Kumar Singh
Flow-Opt learns joint multi-robot trajectories, then uses a differentiable optimization-based safety filter to correct constraint violations. A learned initializer warm-starts the solver. In 2-D tests with 32 robots, it reports average planning time of 0.2966 seconds versus 48.1758 for MMD, with both at 100% success. The method assumes integrator-style robots and applies post-hoc time scaling for velocity and acceleration limits.
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