Robotics tools in C++11. Implements soft real time arm drivers for Kuka LBR iiwa plus V-REP, ROS, Constrained Optimization based planning, Hand Eye Calibration and Inverse Kinematics integration.
Setup Ubuntu 18.04, 16.04 and 14.04 with machine learning and robotics software plus user configuration. Includes ceres tensorflow ros caffe vrep eigen cudnn and cuda plus many more.
🤖 A motion planning MATLAB & V-rep implementation for the KUKA LBR iiwa robotic arm, performing null-space reconfiguration for obstacle avoidance.
Reinforcement Learning Demos
Use python and Vrep to do the path planning for ur5 robot
✏️ Simulation of UR5 robot assembly using vrep and python
This project implements a simulated grasp-and-lift process in V-REP using the Barrett Hand, with an interface through a python remote API.
CoppeliaSim control of various robots through remote API (Python) connection. UR5 industry-setting simulations.
A Reinforcement Learning framework for the NAO robot
Simple Pick And Place Matlab Script using UR10 robotic arm in Vrep
This contain a drone simulated in V-REP (CoppeliaSim)
Matlab and V-REP application of a Hybrid Vision/Force controller for da Vinci surgical robot project for Medical Robotics course 2019-2020
Reinforcement Learning in Vrep
Implementation of the SWEVO paper: "Decentralised Aerial Swarm for Adaptive and Energy Efficient Transport of Unknown Loads".
Learning various robotic manipulations tasks of the UR3
MSc Project aimed at finding an alternative way of representing robot actions. We evaluate several machine learning models to control a simulated 7-joint robotic arm using solely a wrist mounted camera as input.
The aim of this project is to use a down facing camera as a range and bearing sensor for a quadcopter for localization purposes. The environment and robot is simulated in a robot simulator V-REP, the environment consists of a 10mx10m grid with colored markers placed at regular intervals. Performance of different algorithms for marker detection i...
University group project concerning the comparison between the classical and the modified Denavit-Hartenberg convention in Newton-Euler algorithm, and the design of persistently exciting trajectories for the dynamic coefficients identification for the KUKA LWR IV+.
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