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Multi-Robot Trajectory Optimization

Project for Optimal Control and Reinforcement Learning (16-745) course at CMU. Centralized multi-robot offline planner set up as a trajectory optimization problem. Given a set of kinematic collision-free paths for each robot, the controller tries to optimize a safe, smooth, and dynamically feasible local trajectory that can be directly executed on all robots online using DIRCOL and ALTRO

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Project for Optimal Control and Reinforcement Learning (16-745) course at CMU. Solving nonlinear trajectory optimization problem for multiple robot arms in a workspace.

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