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Run-Time Monitoring of Machine Learning for Robotic Perception: A Survey of Emerging Trends
As deep learning continues to dominate all state-of-the-art computer vis...
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Semantics for Robotic Mapping, Perception and Interaction: A Survey
For robots to navigate and interact more richly with the world around th...
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A Systematic Approach to Computing the Manipulator Jacobian and Hessian using the Elementary Transform Sequence
The elementary transform sequence (ETS) provides a universal method of d...
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NEO: A Novel Expeditious Optimisation Algorithm for Reactive Motion Control of Manipulators
We present NEO, a fast and purely reactive motion controller for manipul...
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Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience
Manipulating deformable objects, such as fabric, is a long standing prob...
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Object-Independent Human-to-Robot Handovers using Real Time Robotic Vision
We present an approach for safe and object-independent human-to-robot ha...
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EGAD! an Evolved Grasping Analysis Dataset for diversity and reproducibility in robotic manipulation
We present the Evolved Grasping Analysis Dataset (EGAD), comprising over...
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Maximising Manipulability During Resolved-Rate Motion Control
Resolved-rate motion control of redundant serial-link manipulators is co...
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Robot Navigation in Unseen Spaces using an Abstract Map
Human navigation in built environments depends on symbolic spatial infor...
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Model-free vision-based shaping of deformable plastic materials
We address the problem of shaping deformable plastic materials using non...
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Predicting Target Feature Configuration of Non-stationary Objects for Grasping with Image-Based Visual Servoing
In this paper we consider the problem of the final approach stage of clo...
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What can robotics research learn from computer vision research?
The computer vision and robotics research communities are each strong. H...
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Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation
We propose a new visual object detector evaluation measure which not onl...
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Multi-View Picking: Next-best-view Reaching for Improved Grasping in Clutter
Camera viewpoint selection is an important aspect of visual grasp detect...
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Distinguishing Refracted Features using Light Field Cameras with Application to Structure from Motion
Robots must reliably interact with refractive objects in many applicatio...
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The Limits and Potentials of Deep Learning for Robotics
The application of deep learning in robotics leads to very specific prob...
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Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach
This paper presents a real-time, object-independent grasp synthesis meth...
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Assisted Control for Semi-Autonomous Power Infrastructure Inspection using Aerial Vehicles
This paper presents the design and implementation of an assisted control...
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Sim-to-real Transfer of Visuo-motor Policies for Reaching in Clutter: Domain Randomization and Adaptation with Modular Networks
A modular method is proposed to learn and transfer visuo-motor policies ...
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Visual Servoing from Deep Neural Networks
We present a deep neural network-based method to perform high-precision,...
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Episode-Based Active Learning with Bayesian Neural Networks
We investigate different strategies for active learning with Bayesian de...
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Mirrored Light Field Video Camera Adapter
This paper proposes the design of a custom mirror-based light field came...
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Modular Deep Q Networks for Sim-to-real Transfer of Visuo-motor Policies
While deep learning has had significant successes in computer vision tha...
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The ACRV Picking Benchmark (APB): A Robotic Shelf Picking Benchmark to Foster Reproducible Research
Robotic challenges like the Amazon Picking Challenge (APC) or the DARPA ...
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Exploiting Temporal Information for DCNN-based Fine-Grained Object Classification
Fine-grained classification is a relatively new field that has concentra...
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Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks
We present a novel deep convolutional neural network (DCNN) system for f...
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Towards Vision-Based Deep Reinforcement Learning for Robotic Motion Control
This paper introduces a machine learning based system for controlling a ...
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Subset Feature Learning for Fine-Grained Category Classification
Fine-grained categorisation has been a challenging problem due to small ...
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Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification
We propose a local modelling approach using deep convolutional neural ne...
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