Pinned Repositories
Adaptive_Sliding_Mode_Control_of_Aerial_Manipulator
Adaptive Sliding Mode Control
AtmosphericFlightControlHW1
Gust Modeling and SISO Flight Control Design for Fixed Wing UAV
AutonomousControl
Autonomous flight control algorithms for quadrotor uavs, simulation and testing in MatLab/Simulink and SITL, px4, flightmare, ROS and Gazebo (Currently in development)
Cartesian_Impedance_Control_Aerial_Manipulator
Cartesian Impedance Control of Quadrotor with a Robotic Arm
Flying-Car-and-Autonomous-Flight-Engineer
Flying Car and Autonomous Flight Engineer Nanodegree, Udacity
IFAC_Force_Control_Cooperative_Aerial_Manipulation_with_Quadrotor_Visualization_Matlab
Cooperative aerial load transport with force control IFAC 2018
Intro-to-Self-Driving-Cars
Intro to Self Driving Cars Nano Degree Udacity
LCSS_2019_Concurrent_Learning
Cooperative Manipulation of an Unknown Payload With Concurrent Mass and Drag Force Estimation. Thapa, S., Self, R. V., Kamalapurkar, R., & Bai, H. (2019). , IEEE Control Systems Letters, 3(4), 907-912.
Output-LQR-Design-for-Fixed-UAV--AtmosphericFlightControlHW3
Output LQR Design for Fixed Wing UAV and Gust response analysis
Quadrotor-Traj-Generation-and-Control
sandeshthapa's Repositories
sandeshthapa/drone-load-transportation
sandeshthapa/Model-Predictive-Control-1
Nonlinear model predictive controller (NMPC) to steer a car around a track in a simulator
sandeshthapa/acado
ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization.
sandeshthapa/AutonomousDrivingCookbook
Scenarios, tutorials and demos for Autonomous Driving
sandeshthapa/controlpy
Python controls
sandeshthapa/DSL_ARDrone_L1_controller
L1 adaptive output feedback controller for ARDrone
sandeshthapa/ecen674
small fixed wing UAV simulator
sandeshthapa/Hands-On-Reinforcement-Learning-with-Python
Hands-On Reinforcement Learning with Python, published by Packt
sandeshthapa/interview-preparation
Preparation for interview.
sandeshthapa/Intro-to-Self-Driving-Cars-1
Self driving cars of udacity
sandeshthapa/masters-thesis
Model predictive control of micro aerial vehicle using onboard microcontroller
sandeshthapa/Model-Predictive-Control
This project is to use Model Predictive Control (MPC) to drive a car in a game simulator. The server provides reference waypoints (yellow line in the demo video) via websocket, and we use MPC to compute steering and throttle commands to drive the car. The solution must be robust to 100ms latency, since it might encounter in real-world application.
sandeshthapa/MPC
sandeshthapa/NeeleyThesisCode
Quadrotor Code Provided By Wil Neeley Used In His Thesis (Defended June, 2015)
sandeshthapa/planning_books_1
记录:规划,决策,机器学习,编程的书籍
sandeshthapa/turtlebot2_demo