Ogunniran

Pinned Repositories

Deep_learning_for_detectin_robotic_grasps
Code from Robot Learning Lab, Cornell in paper Deep Learning for Detecting Robotic Grasps
Language:MATLAB00
ForkLift-Path-Tracking
forklift path tracking
Language:C++00
ggcnn
Generative Grasping CNN from "Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach" (RSS 2018)
Language:Python00
invite-robotics
Integration of Motoman CSDA10f dual arm robot with ROS, Moveit and Gazebo, with aims of creating a robotics developing platform for Invite GmbH, pre-configured to be simple to use and learn.
Language:C++00
omages
We present Object Images (Omages): An homage to the classic Geometry Images.
Language:Jupyter Notebook00
robot-grasp-detection
Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.
Language:Python00
synthetic-computer-vision
A list of synthetic dataset and tools for computer vision
Language:Python00
intera_head_media_example
An exemplary Node.js sever streaming media to the Sawyer head.
Language:Python00

Ogunniran's Repositories

Ogunniran/Deep_learning_for_detectin_robotic_grasps
Code from Robot Learning Lab, Cornell in paper Deep Learning for Detecting Robotic Grasps
Language:MATLAB
Ogunniran/ForkLift-Path-Tracking
forklift path tracking
Language:C++
Ogunniran/ggcnn
Generative Grasping CNN from "Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach" (RSS 2018)
Language:Python
Ogunniran/invite-robotics
Integration of Motoman CSDA10f dual arm robot with ROS, Moveit and Gazebo, with aims of creating a robotics developing platform for Invite GmbH, pre-configured to be simple to use and learn.
Language:C++
Ogunniran/omages
We present Object Images (Omages): An homage to the classic Geometry Images.
Ogunniran/robot-grasp-detection
Detecting robot grasping positions with deep neural networks. The model is trained on Cornell Grasping Dataset. This is an implementation mainly based on the paper 'Real-Time Grasp Detection Using Convolutional Neural Networks' from Redmon and Angelova.
Language:Python
Ogunniran/synthetic-computer-vision
A list of synthetic dataset and tools for computer vision
Language:Python