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

Complex robot maze navigation using image classification and ROS

This project is a ROS based mobile robot navigator using sign recognition based on image classification. It has two major components: Image classification based sign recognition using SVM classifier: A set of 300 images were trained offline to classify 5 different road signs (turn right, turn left, stop, turn around, goal). SVM classifier was used tp obtain an accuracy of over 90% on unseen and diverse set of images taken

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