Industrial Robots
16 papers with code • 0 benchmarks • 1 datasets
An industrial robot is a robot system used for manufacturing. Industrial robots are automated, programmable and capable of movement on three or more axes.
Benchmarks
These leaderboards are used to track progress in Industrial Robots
Synthetic Object Preference Adaptation Data
Most implemented papers
The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints
We show that a mild relaxation of the task and workspace constraints implicit in existing object grasping datasets can cause neural network based grasping algorithms to fail on even a simple block stacking task when executed under more realistic circumstances.
Introducing the Robot Vulnerability Database (RVD)
Cybersecurity in robotics is an emerging topic that has gained significant traction.
You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration
The canonical object representation is learned solely in simulation and then used to parse a category-level, task trajectory from a single demonstration video.
Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
We extensively evaluate our approaches with a total of more than 25, 000 physical test grasps, studying a range of simulation conditions and domain adaptation methods, including a novel extension of pixel-level domain adaptation that we term the GraspGAN.
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
swchui/VTFSA
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In this work, we investigate the question of whether touch sensing aids in predicting grasp outcomes within a multimodal sensing framework that combines vision and touch.
An Internet of Things humanoid robot teleoperated by an open source Android application
The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human interaction.
Hardware Conditioned Policies for Multi-Robot Transfer Learning
taochenshh/hcp
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NeurIPS 2018
In tasks where knowing the agent dynamics is important for success, we learn an embedding for robot hardware and show that policies conditioned on the encoding of hardware tend to generalize and transfer well.
Learning to combine primitive skills: A step towards versatile robotic manipulation
rstrudel/rlbc
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Manipulation tasks such as preparing a meal or assembling furniture remain highly challenging for robotics and vision.
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
clvrai/furniture
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The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and accelerating the automation of complex manipulation tasks.
Artificial Intelligence Control in 4D Cylindrical Space for Industrial Robotic Applications
Since path optimization is the core of any search algorithms, including A*, the 4D cylindrical grid provides for a search space that can embed further knowledge in form of cell properties, including the presence of obstacles and volumetric occupancy of the entire industrial robot body for obstacle avoidance applications.
