Workshop resources for simulating UR manipulators with Nvidia Isaac Sim and ROS 2 for ROSCon ES 2024.
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Updated
Sep 17, 2024 - Python
Workshop resources for simulating UR manipulators with Nvidia Isaac Sim and ROS 2 for ROSCon ES 2024.
Simple ros2 grasp service
A project on using gestures to move manipulator in Moveit using MTC stages
MATLAB Robotic Manipulator Control and User Interface with App Designer and Arduino.
This is a curated list of "Embodied AI or robot with Large Language Models" research. Watch this repository for the latest updates! 🔥
Service robot development for RoboCup @Home OPL
🤖 Simulate and control two Universal Robots arms simultaneously using NVIDIA Isaac Sim. Explore real-time control, collision avoidance, and path planning in a digital twin environment.
Assignments for Modeling and Control of Manipulators course
An advanced robotics initiative harnessing Kinect's computer vision capabilities for precise object detection and manipulation, coupled with robust autonomous navigation and path planning technologies. Powered by an Arduino for seamless hardware control and real-time responsiveness.
This repository showcases my work in Planning for Autonomous Robots, focusing on planning techniques applied to industrial robots such as KUKA. The work involves leveraging Moveit in Gazebo for proficient execution of pick and place operations. Throughout the course, I also learned various 2D search algorithms, ranging from A* to RRT and its types.
This repository showcases my project focused on implementing a pick and place operation using a 9 Degrees of Freedom (DOF) mobile manipulator robot in Gazebo, along with Rviz visualizations. The application is geared towards cleaning in compact and cluttered environments.
Implementation of Gravity Compensation Algorithm, Recursive Newton-Euler Algorithm (RNEA), PD Control and Computed Torque Control of 1R, 2R, 2R-NP, 3R and RP Robotic Arms on Simulink
This repository contains Python scripts for simulating the movements of a robotic arm in both 3D and 4D environments. The simulations demonstrate the arm's capability to track complex trajectories and perform intricate movements, showcasing the potential applications in real-life robotics.
This project focuses on training robots to grasp everyday objects accurately. We gather a unique point cloud dataset using an iPhone's LiDAR and process it with Polycam. We develop a PointNet model from scratch to perform multi-class classification and part-segmentation, guiding the robot on where to grasp objects.
Inverse Dynamics, PD, Passivity based, passivity-Based Adaptive and Passivity-Based Robust Control of a two-link revolute-joint planar robot
Honors Section for Robotics: Mobility and Manipulation @ CU-ICAR
In the realm of robotics innovation, I undertook the design and creation of an exceptional FSR board. This board boasts a remarkable ability: to adeptly decipher analog-to-digital signals and glean insights from pressure sensors. The convergence of these features proves particularly pivotal in the domain of robotic manipulation.
Autonomy: Mobility and Manipulation @ CU-ICAR
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