Learning inverse dynamics of 7-DOF Robot Arm

An accurate estimation for the inertial parameters of a robot manipulator is essential for many modern manipulator control algorithms including calculating inverse dynamics of the robot. This project implements a unique approach for numerically determining regressor matrix without explicitly deriving the equations. This is accomplished using state of the art articulated body algorithms such as Featherstone’s and an approximate model of the robot usually captured by a URDF file. The

Vehicle Control for Autonomous Driving

Implementation of Longitudinal and Lateral control to autonomously navigate a car through a set of given way points using Stanley Control for Lateral Control and PID control for Longitudinal Control. This project was implemented on CARLA simulator based on unreal engine.  Input to the system is given waypoints in the form of a text file which specifiy the desired position and velocity along the path Output is throttle_output (betwwen 0 and 1),

End to end imitation learning of dynamically unstable systems

Pixels to Controls is a widely studies topic in the field of controls and machine learning. This project aims to implement behavior based cloning and imitation learning approaches for dynamically unstable systems. The first part of this project has been implemented on ROS and Gazebo. For Golem Krang robot(shown above), an expert LQR controller has been developed which tracks a certain trajectory in simulation. In this ongoing project, next step