Perception, Planning and Controlling
# 1. Part 1
# 1.1 for conda environment
conda install -c conda-forge ffmpeg
# 1.2 for python environment
pip install ffmpeg-python
# 2. Part 2
pip install pypng casadi
# Use A* find a path and Spline to interpolate the path
python test/gridmap_astar.py
# Use mpc to control a differential drive model
python test/motion_planning.py
# Test the circle obstacle and laser sensor detection
python envs/shapemap.py
# Test decomp_utils of pybind version
python test/gridmap_anyshape_test.py
https://github.com/libai1943/CartesianPlanner
https://github.com/icsl-Jeon/traj_gen
https://github.com/richardos/occupancy-grid-a-star
https://github.com/Shunichi09/PythonLinearNonlinearControl
https://github.com/tud-amr/localPlannerBench
https://github.com/kohonda/mpc_tracker_ros
https://github.com/tomcattiger1230/CasADi_MPC_MHE_CPP
https://github.com/alexliniger/MPCC
https://github.com/tud-amr/amr-lmpcc
https://github.com/jan9419/Generic_NMPC_Cpp
https://github.com/taewankim1/sequential_convex_programming*
https://github.com/samarth-kalluraya/Obstacle_Avoidance_MPC_Controller_A_star_Planning
https://github.com/xinjie-liu/SafeMPC_ObstacleAvoidance
https://github.com/jaidevshriram/Robotics-Navigation
https://github.com/Vassil17/Safe_Nonholonomic_MPC
https://github.com/helgeanl/GP-MPC
https://github.com/xinjie-liu/SafeMPC_ObstacleAvoidance
https://github.com/epfl-lasa/dynamic_obstacle_avoidance*
https://github.com/libai1943/CartesianPlanner*
https://github.com/StanfordASL/ccscp
https://github.com/HybridRobotics/cbf
https://github.com/nvidia-isaac/nvblox
https://github.com/StarryN/Galaxy