LT310's Stars
S-Dafarra/variable-height-double-pendulum
Code for the paper "Non-Linear Trajectory Optimization for Large Step-Ups: Application to the Humanoid Robot Atlas"
yunifuchioka/opt-mimic-traj-opt
Trajectory optimization code for the paper "OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviors"
MichaelFYang/far_planner
Fast, Attemptable Route Planner for Navigation in Known and Unknown Environments
jacken3/Reinforcement-Learning_Path-Planning
jacken3/PathPlanning
NNaert/Python-controlled-Braccio-robot-arm
xhcdream/KCGN
AAAI-2021
chauncygu/Safe-Reinforcement-Learning-Baselines
The repository is for safe reinforcement learning baselines.
jsztompka/MultiAgent-PPO
Proximal Policy Optimization with Beta distribution - uses multi agent Unity ML Tennis
faildeny/Multi_Agent_PPO
Multi agent PPO implementation in Pytorch for Unity ML Agents environments.
VorteX-co/VAUV
VorteX AUV
PickNikRobotics/rviz_visual_tools
C++ API wrapper for displaying shapes and meshes in Rviz
ange-yaghi/simple-2d-constraint-solver
Simple physics simulator with support for rigid bodies, force generators and constraints.
zain18jan2000/Object-Detection-Using-YOLOv5
Python Based Implementation Of YOLOv5 for Object Detection
zain18jan2000/NON-MAXIMUM-SUPPRESION-WITH-NUMPY
atb033/multi_agent_path_planning
Python implementation of a bunch of multi-robot path-planning algorithms.
moos-tutorials/00-my-first-moos-project
Installing and running a simple moos project
balamuruganky/EKF_IMU_GPS
Extended Kalman Filter predicts the GNSS measurement based on IMU measurement
hgpvision/Indirect_EKF_IMU_GPS
基于间接卡尔曼滤波的IMU与GPS融合MATLAB仿真(IMU与GPS数据由仿真生成)
gilbertz/GPS_Milemeter_IMU_EKFLocation
采用gps、里程计和电子罗盘作为定位传感器,EKF作为多传感器的融合算法,最终输出目标的滤波位置
soarbear/imu_ekf
6-axis(3-axis acceleration sensor+3-axis gyro sensor) IMU fusion with Extended Kalman Filter.
Optimal-Control-16-745/lecture-notebooks-2022
tahanakabi/DRL-for-microgrid-energy-management
We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.
savinay95n/Reinforcement-learning-Algorithms-and-Dynamic-Programming
Reinforcement learning Algorithms such as SARSA, Q learning, Actor-Critic Policy Gradient and Value Function Approximation were applied to stabilize an inverted pendulum system and achieve optimal control. So essentially, the concept of Reinforcement Learning Controllers has been established. The Reinforcement Learning Controllers have been compared on the basis of performance and efficiency and they are separately compared with the classical Linear Quadratic Regulator Controller. Each of the RL controller have been integrated with a Swing up controller. A virtual switch toggles between the Swing up controller and the RL controller automatically, based on the value of the angular deviation theta with respect to the vertical plane. My research paper and my undergraduate thesis have been uploaded for reference. All the codes have also been uploaded.
Rajesh-Siraskar/Reinforcement-Learning-for-Control-of-Valves
This project uses DDPG for "optimal" control of non-linear valves. Uses MATLAB and Simulink
mail-ecnu/Reinforcement-Learning-and-Optimal-Control
eleurent/phd-bibliography
References on Optimal Control, Reinforcement Learning and Motion Planning
im1235/ISAC
Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning
ignaciotb/UWExploration
google-deepmind/mujoco_menagerie
A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.