2017 Robotic Instrument Segmentation Challenge

18 Feb 20192 code implementations

In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance comparison.

Deep Residual Learning for Instrument Segmentation in Robotic Surgery

24 Mar 20171 code implementation

Detection, tracking, and pose estimation of surgical instruments are crucial tasks for computer assistance during minimally invasive robotic surgery.

POSE ESTIMATION

Composable Deep Reinforcement Learning for Robotic Manipulation

19 Mar 20181 code implementation

Second, we show that policies learned with soft Q-learning can be composed to create new policies, and that the optimality of the resulting policy can be bounded in terms of the divergence between the composed policies.

Q-LEARNING

Behavior Trees in Robotics and AI: An Introduction

31 Aug 20173 code implementations

A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game.

Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning

3 Mar 20182 code implementations

Semantic segmentation of robotic instruments is an important problem for the robot-assisted surgery.

POSE ESTIMATION SEMANTIC SEGMENTATION

RLBench: The Robot Learning Benchmark & Learning Environment

26 Sep 20191 code implementation

We present a challenging new benchmark and learning-environment for robot learning: RLBench.

FEW-SHOT LEARNING IMITATION LEARNING MULTI-TASK LEARNING

Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation

22 Jun 20183 code implementations

In this paper we present Dense Object Nets, which build on recent developments in self-supervised dense descriptor learning, as a consistent object representation for visual understanding and manipulation.

A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder

2 Nov 20173 code implementations

The detection of anomalous executions is valuable for reducing potential hazards in assistive manipulation.

SkiMap: An Efficient Mapping Framework for Robot Navigation

19 Apr 20171 code implementation

We present a novel mapping framework for robot navigation which features a multi-level querying system capable to obtain rapidly representations as diverse as a 3D voxel grid, a 2. 5D height map and a 2D occupancy grid.

ROBOT NAVIGATION

End-to-End Robotic Reinforcement Learning without Reward Engineering

16 Apr 20191 code implementation

In this paper, we propose an approach for removing the need for manual engineering of reward specifications by enabling a robot to learn from a modest number of examples of successful outcomes, followed by actively solicited queries, where the robot shows the user a state and asks for a label to determine whether that state represents successful completion of the task.