lee-ck's Stars
casadi/casadi
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
osqp/osqp
The Operator Splitting QP Solver
PyDMD/PyDMD
Python Dynamic Mode Decomposition
Shunichi09/PythonLinearNonlinearControl
PythonLinearNonLinearControl is a library implementing the linear and nonlinear control theories in python.
whoenig/libMultiRobotPlanning
Library with search algorithms for task and path planning for multi robot/agent systems
utiasDSL/safe-control-gym
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
ByungKwanLee/MoAI
[ECCV 2024] Official PyTorch implementation code for realizing the technical part of Mixture of All Intelligence (MoAI) to improve performance of numerous zero-shot vision language tasks.
dynamicslab/pykoopman
A package for computing data-driven approximations to the Koopman operator.
MizuhoAOKI/python_simple_mppi
Python implementation of MPPI (Model Predictive Path-Integral) controller to understand the basic idea. Mandatory dependencies are numpy and matplotlib only.
rdeits/iris-distro
Iterative Regional Inflation by SDP
ByungKwanLee/Full-Segment-Anything
This is Pytorch Implementation Code for adding new features in code of Segment-Anything. Here, the features support batch-input on the full-grid prompt (automatic mask generation) with post-processing: removing duplicated or small regions and holes, under flexible input image size
ByungKwanLee/CoLLaVO
[ACL 2024 Findings] Official PyTorch Implementation code for realizing the technical part of CoLLaVO: Crayon Large Language and Vision mOdel to significantly improve zero-shot vision language performances
lee-ck/Model-Predictive-Control
Model predictive control (MPC) of an autonomous vehilcle for lane tracking and obstacle avoidance with ACADO toolkit
GaloisInc/dlkoopman
A general-purpose Python package for Koopman theory using deep learning.
UMich-CURLY/Lie-MPC-AMVs
Convex Geometric Trajectory Tracking using Lie Algebraic MPC for Autonomous Marine Vehicles
cvxgrp/fastpathplanning
A fast algorithm for finding an optimal path in a collection of safe boxes
sriram-2502/KoopmanMPC_Quadrotor
Develop a Koopman operator based MPC for controlling a quadrotor
hungrepo/path-following-Matlab
path following for autonomous robotic vehicles
rllab-snu/R3-Driving-Dataset
enhatem/quadrotor_mpc_acados
MPC implementation for quadrotors using acados
Yangyangii/pytorch-practice
pytorch basic
boranzhao/robust_ccm_tube
Tube-certified nonlinear tracking with robust control contraction metrics
resilient-swarms/ASVLite
Simulator of a swarm of surface vehicles in marine environments
ctu-mrs/mrs_uav_unreal_simulation
JianZhou1212/learning-based-rigid-tube-rmpc
This is the MATLAB code for tube robust MPC with uncertainty quantification
ByungKwanLee/Causal-Unsupervised-Segmentation
Official PyTorch Implementation code for realizing the technical part of Causal Unsupervised Semantic sEgmentation (CAUSE) to improve performance of unsupervised semantic segmentation. (Under Review)
lee-ck/Quadrotor-NMPC-based-Obstacle-Avoidance
NMPC for Quadrotor - Dynamic, static obstacle avoidance & Landing on box
JohannesAutenrieb/CBF_ACC
This collection of MATLAB scripts intends to study the performance of state-constrained controllers utilizing control barrier functions in the context of adaptive cruise control.
qypalice/USV_DeepKoopman
adrianomcr/skid_steering_model
Matlab implementation of a dynamic model for a skid steering platform with 4 wheels