VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
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Updated
May 8, 2024 - Python
VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models
Antipodal Robotic Grasping using GR-ConvNet. IROS 2020.
paper list of robotic grasping and some related works
"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer
NeurIPS 2022 Paper "VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation"
Baxter Pick and Place using GR-ConvNet. IROS 2020.
Hector Quadrotor with MoveIt! Motion Planning Framework
myGym enables fast prototyping of RL in the area of robotic manipulation and navigation.You can train different robots, in several environments on various tasks. There is automatic evaluation and benchmark tool. From version 2.1 there is support for multi-step tasks, multi-reward training and multi-network architectures.
Robotic Manipulation - Learned in the Real World
The RObotic MAnipulation Network
The project demonstrates an advanced dynamic manipulation strategy by soft gripper called flex-and-flip. The technique is targeted at flexible, thin objects and applied to obtaining secure, pinch grasps on them.
A collection of RL gym environments built with PyBullet. In these environments, the agent needs to learn to grasp deformable object such as shoe insoles or pillows.
Official PyTorch implementation of "Entity-Centric Reinforcement Learning for Object Manipulation from Pixels", Haramati et al., ICLR 2024
Low-cost platform to explore concepts in robotic manipulation
Deep Reinforcement Learning for Robotic Pushing and Picking in Cluttered Environment
mBEST: Realtime detection of DLOs via minimal bending energy skeleton pixel traversals
Deep Robotic Grasping using Generative Residual Convolutional Neural Networks that can generate robust antipodal grasps from RGB-D input images at real-time
Parallel-in-Time Physics Simulation for Robotic Manipulation
Learning a Generative Transition Model for Uncertainty-Aware Robotic Manipulation
Robot Grasping in Cluttered Environment with DDPG&Affordance
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