PythonLinearNonLinearControl is a library implementing the linear and nonlinear control theories in python.
Python implementation of MPPI (Model Predictive Path-Integral) controller to understand the basic idea. Mandatory dependencies are numpy and matplotlib only.
Model Predictive Path Integral (MPPI) with approximate dynamics implemented in pytorch
A GPU implementation of Model Predictive Path Integral (MPPI) control that uses a probabilistic traversability model for planning risk-aware trajectories.
Templated C++/CUDA implementation of Model Predictive Path Integral Control (MPPI)
Nullspace MPC: A novel multi-objective control framework for explicitly handling task priorities, implemented in ROS Noetic for a Swerve Drive Robot.
[IROS 2024] MPPI (Model Predictive Path-Integral) Controller for a Swerve Drive Robot
Model Predictive Path Integral Control (MPPI) with PyTorch
libmpc++ is a C++ header-only library to solve linear and non-linear MPC
25 path-tracking algorithms are (going to be) implemented with python.
We present the first successful deployment of a whole-body sampling-based MPC system on a real-world quadruped robot. Our approach enables real-time, contact-rich locomotion and manipulation using a single control policy derived from Model-Predictive Path Integral (MPPI) control.
[ICRA2024] Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles
Autonomous UAV navigation in GNSS-denied indoor spaces with no prior map: stereo VIO (MSCKF) and lidar-inertial odometry with map-based relocalization (SLAM), 3D occupancy mapping, D* Lite path planning and GPU MPPI obstacle avoidance. PX4 + ROS 2 + Gazebo SITL, DARPA SubT Urban.
Colab notebooks showcasing experiments on MPPI (model predictive path integral control) and CBF (control barrier function). Utilizes jax to accelerate computation.
Mapping, localization and using the navigation stack with ROS2 Jazzy
Adaptive importance sampling modification to MPPI
off-road navigation simulator for benchmarking planning algorithms
Adaptive control for skid-steer robots using GP-enhanced MPPI for robust navigation and obstacle avoidance on diverse terrains.
Real-time probabilistic inference-based motion planning for autonomous driving with MPPI
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