Robot Manipulation
83 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find Robot Manipulation models and implementationsMost implemented papers
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.
Motion-based Object Segmentation based on Dense RGB-D Scene Flow
Our model jointly estimates (i) the segmentation of the scene into an unknown but finite number of objects, (ii) the motion trajectories of these objects and (iii) the object scene flow.
A Mixed Classification-Regression Framework for 3D Pose Estimation from 2D Images
Since 3D pose is a continuous quantity, a natural formulation for this task is to solve a pose regression problem.
Video Object Segmentation using Teacher-Student Adaptation in a Human Robot Interaction (HRI) Setting
A human teacher can show potential objects of interest to the robot, which is able to self adapt to the teaching signal without providing manual segmentation labels.
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.
Recognizing Object Affordances to Support Scene Reasoning for Manipulation Tasks
Unfortunately, the top performing affordance recognition methods use object category priors to boost the accuracy of affordance detection and segmentation.
$H_\infty$ Model-free Reinforcement Learning with Robust Stability Guarantee
In this paper, we introduce and extend the idea of robust stability and $H_\infty$ control to design policies with both stability and robustness guarantee.
Learning Structured Representations of Spatial and Interactive Dynamics for Trajectory Prediction in Crowded Scenes
Context plays a significant role in the generation of motion for dynamic agents in interactive environments.