no code implementations • 12 Nov 2021 • Chuyuan Tao, Hunmin Kim, HyungJin Yoon, Naira Hovakimyan, Petros Voulgaris
For a nonlinear stochastic path planning problem, sampling-based algorithms generate thousands of random sample trajectories to find the optimal path while guaranteeing safety by Lagrangian penalty methods.
no code implementations • 27 Mar 2021 • Hunmin Kim, HyungJin Yoon, Wenbin Wan, Naira Hovakimyan, Lui Sha, Petros Voulgaris
To incorporate this new safety concept in control problems, we formulate a feasibility maximization problem that adopts additional (virtual) input horizons toward the alternative missions on top of the input horizon toward the primary mission.