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Found 10 papers, 6 papers with code
World Models for General Surgical Grasping
Our learned visuomotor policy handles: i) unseen objects, including 5 types of target grasping objects and a robot gripper, in unstructured real-world surgery environments, and ii) disturbances in perception and control.
Towards Safe Control of Continuum Manipulator Using Shielded Multiagent Reinforcement Learning
Continuum robotic manipulators are increasingly adopted in minimal invasive surgery.
Hyperparameter Auto-tuning in Self-Supervised Robotic Learning
Insufficient learning (due to convergence to local optima) results in under-performing policies whilst redundant learning wastes time and resources.
Pose-based Modular Network for Human-Object Interaction Detection
We contribute a Pose-based Modular Network (PMN) which explores the absolute pose features and relative spatial pose features to improve HOI detection and is fully compatible with existing networks.
Ranked #23 on
Human-Object Interaction Detection
on V-COCO
A Graph Attention Spatio-temporal Convolutional Network for 3D Human Pose Estimation in Video
Spatio-temporal information is key to resolve occlusion and depth ambiguity in 3D pose estimation.
Ranked #11 on
3D Human Pose Estimation
on HumanEva-I
Visual-Semantic Graph Attention Networks for Human-Object Interaction Detection
Few works have studied the disambiguating contribution of subsidiary relations made available via graph networks.
Towards More Sample Efficiency in Reinforcement Learning with Data Augmentation
Deep reinforcement learning (DRL) is a promising approach for adaptive robot control, but its current application to robotics is currently hindered by high sample requirements.
Invariant Transform Experience Replay: Data Augmentation for Deep Reinforcement Learning
Our work demonstrates that invariant transformations on RL trajectories are a promising methodology to speed up learning in deep RL.
Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation through Grounded Anomaly Classification and Recovery Policies
Robot manipulation is increasingly poised to interact with humans in co-shared workspaces.
A 3D Object Detection and Pose Estimation Pipeline Using RGB-D Images
This paper proposes a robust 3D object detection and pose estimation pipeline based on RGB-D images, which can detect multiple objects simultaneously while reducing false positives.
