Robot Manipulation
48 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Robot Manipulation
YCB-Slide
Most implemented papers
What Matters in Language Conditioned Robotic Imitation Learning over Unstructured Data
mees/hulc
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We have open-sourced our implementation to facilitate future research in learning to perform many complex manipulation skills in a row specified with natural language.
DeepIM: Deep Iterative Matching for 6D Pose Estimation
liyi14/mx-DeepIM
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ECCV 2018
Estimating the 6D pose of objects from images is an important problem in various applications such as robot manipulation and virtual reality.
SilhoNet: An RGB Method for 6D Object Pose Estimation
gidobot/SilhoNet
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Autonomous robot manipulation involves estimating the translation and orientation of the object to be manipulated as a 6-degree-of-freedom (6D) pose.
Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations
In order to exploit this idea, we introduce a framework whereby an object locomotion policy is initially obtained using a realistic physics simulator.
Learning 3D Dynamic Scene Representations for Robot Manipulation
3D scene representation for robot manipulation should capture three key object properties: permanency -- objects that become occluded over time continue to exist; amodal completeness -- objects have 3D occupancy, even if only partial observations are available; spatiotemporal continuity -- the movement of each object is continuous over space and time.
Mobile Robot Manipulation using Pure Object Detection
griffbr/tfod
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We develop an end-to-end manipulation method based solely on detection and introduce Task-focused Few-shot Object Detection (TFOD) to learn new objects and settings.
VIMA: General Robot Manipulation with Multimodal Prompts
This work shows that we can express a wide spectrum of robot manipulation tasks with multimodal prompts, interleaving textual and visual tokens.
Solving the robot-world hand-eye(s) calibration problem with iterative methods
Robot-world, hand-eye calibration is the problem of determining the transformation between the robot end-effector and a camera, as well as the transformation between the robot base and the world coordinate system.
Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-Stage Task
End-to-end control for robot manipulation and grasping is emerging as an attractive alternative to traditional pipelined approaches.
Neural Task Programming: Learning to Generalize Across Hierarchical Tasks
In this work, we propose a novel robot learning framework called Neural Task Programming (NTP), which bridges the idea of few-shot learning from demonstration and neural program induction.
