MPC-Berkeley/hmpc_raidnet
Implementation of Hierarchical MPC with RAID-Net
This project helps self-driving vehicle engineers and researchers create more efficient motion planners for autonomous vehicles navigating complex environments with multiple interacting agents. It takes in sensor data and environmental parameters, then outputs optimized motion plans that significantly reduce the computation time for collision avoidance while maintaining safety. This is for professionals working on autonomous driving systems or intelligent vehicle research.
No commits in the last 6 months.
Use this if you need to rapidly plan safe trajectories for autonomous vehicles in multi-agent scenarios, significantly cutting down on computational load compared to traditional methods.
Not ideal if you are working on single-agent path planning or in environments where interaction prediction is not a critical factor.
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Python
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Last pushed
Jan 22, 2025
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