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Found 9 papers, 6 papers with code
Self-supervised Transfer Learning for Instance Segmentation through Physical Interaction
To achieve this, we fine-tune an existing DeepMask network for instance segmentation on the self-labeled training data acquired by the robot.
Adaptive Curriculum Generation from Demonstrations for Sim-to-Real Visuomotor Control
We propose Adaptive Curriculum Generation from Demonstrations (ACGD) for reinforcement learning in the presence of sparse rewards.
From Plants to Landmarks: Time-invariant Plant Localization that uses Deep Pose Regression in Agricultural Fields
Agricultural robots are expected to increase yields in a sustainable way and automate precision tasks, such as weeding and plant monitoring.
Deep Detection of People and their Mobility Aids for a Hospital Robot
In this paper, we propose a depth-based perception pipeline that estimates the position and velocity of people in the environment and categorizes them according to the mobility aids they use: pedestrian, person in wheelchair, person in a wheelchair with a person pushing them, person with crutches and person using a walker.
Learning to Singulate Objects using a Push Proposal Network
We present a novel neural network-based approach that separates unknown objects in clutter by selecting favourable push actions.
Choosing Smartly: Adaptive Multimodal Fusion for Object Detection in Changing Environments
Object detection is an essential task for autonomous robots operating in dynamic and changing environments.
Optimization Beyond the Convolution: Generalizing Spatial Relations with End-to-End Metric Learning
To operate intelligently in domestic environments, robots require the ability to understand arbitrary spatial relations between objects and to generalize them to objects of varying sizes and shapes.
The Freiburg Groceries Dataset
In this paper, we address this issue and present a dataset consisting of 5, 000 images covering 25 different classes of groceries, with at least 97 images per class.
Multimodal Deep Learning for Robust RGB-D Object Recognition
Robust object recognition is a crucial ingredient of many, if not all, real-world robotics applications.
