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Safe and Interactive Crowd NavigationThis repository contains the code for our paper SICNav: Safe and Interactive Crowd Navigation using Model Predictive Control and Bilevel Optimization including the CrowdSimPlus Simulator.Website | Repo | IEEE Xplore| arXiv | Video @article{samavi2024sicnav, author={Samavi, Sepehr and Han, James R. and Shkurti, Florian and Schoellig, Angela P.}, journal={IEEE Transactions on Robotics}, title={SICNav: Safe and Interactive Crowd Navigation using Model Predictive Control and Bilevel Optimization}, year={2024}, volume={}, number={}, pages={1-19}, doi={10.1109/TRO.2024.3484634}, url={ a conda environment with Python 3.8.13,Install this package using pip:Install the required libraries:pip install -r requirements.txtClone and install Python-RVO2 library. Note that a compatible version of Cython 0.29.33 will be installed already in step 2. You should only need to run:/Python-RVO2/">pip install -e /Python-RVO2/(Recommended) Install HSL to use advanced solvers in IPOPT, the settings that we use in campc.py make use of a linear solver from HSL, however the code in this repo will work with the default IPOPT settings as well. Instructions: Crowd Navigation AlgorithmsThe following algorithms can be visualized by running the following command in the sicnav/ directory:">python simple_test.py --policy Collision Avoidance MPC (--policy campc) can be configured in sicnav/configs/policy.config to act as the following algorithms described in the paper:SICNav-p (ours): our algorithm with access to privileged information about the humansSICNav-np (ours): our algorithm without access to privileged information about the humansMPC-CVMM: the MPC baseline that does not model human interactivelyDynamic Window Approach (--policy dwa)To train and visualize the Reinforcement Learning algorithms, SARL and RGL, please see the RL_nav/ subdirectory.CrowdSimPlus SimulatorCrowdSimPlus is based on
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