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04/21/2023
Contrastive Language, Action, and State Pre-training for Robot Learning
In this paper, we introduce a method for unifying language, action, and ...
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03/27/2023
Addressing the Challenges of Open-World Object Detection
We address the challenging problem of open world object detection (OWOD)...
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11/08/2022
ParticleNeRF: A Particle-Based Encoding for Online Neural Radiance Fields in Dynamic Scenes
Neural Radiance Fields (NeRFs) learn implicit representations of - typic...
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11/04/2022
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics
Skill-based reinforcement learning (RL) has emerged as a promising strat...
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09/19/2022
Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fields
We show that ensembling effectively quantifies model uncertainty in Neur...
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04/22/2022
Implicit Object Mapping With Noisy Data
Modelling individual objects as Neural Radiance Fields (NeRFs) within a ...
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12/10/2021
Hyperdimensional Feature Fusion for Out-Of-Distribution Detection
We introduce powerful ideas from Hyperdimensional Computing into the cha...
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12/10/2021
Zero-Shot Uncertainty-Aware Deployment of Simulation Trained Policies on Real-World Robots
While deep reinforcement learning (RL) agents have demonstrated incredib...
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09/16/2021
Evaluating the Impact of Semantic Segmentation and Pose Estimation on Dense Semantic SLAM
Recent Semantic SLAM methods combine classical geometry-based estimation...
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09/10/2021
A Holistic Approach to Reactive Mobile Manipulation
We present the design and implementation of a taskable reactive mobile m...
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08/19/2021
FSNet: A Failure Detection Framework for Semantic Segmentation
Semantic segmentation is an important task that helps autonomous vehicle...
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07/21/2021
Bayesian Controller Fusion: Leveraging Control Priors in Deep Reinforcement Learning for Robotics
We present Bayesian Controller Fusion (BCF): a hybrid control strategy t...
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05/07/2021
Probabilistic Visual Place Recognition for Hierarchical Localization
Visual localization techniques often comprise a hierarchical localizatio...
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04/03/2021
Uncertainty for Identifying Open-Set Errors in Visual Object Detection
Deployed into an open world, object detectors are prone to a type of fal...
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01/02/2021
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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12/23/2020
SWA Object Detection
Do you want to improve 1.0 AP for your object detector without any infer...
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11/16/2020
Online Monitoring of Object Detection Performance Post-Deployment
Post-deployment, an object detector is expected to operate at a similar ...
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09/18/2020
Performance Monitoring of Object Detection During Deployment
Performance monitoring of object detection is crucial for safety-critica...
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09/11/2020
The Robotic Vision Scene Understanding Challenge
Being able to explore an environment and understand the location and typ...
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08/31/2020
VarifocalNet: An IoU-aware Dense Object Detector
Accurately ranking a huge number of candidate detections is a key to the...
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08/03/2020
BenchBot: Evaluating Robotics Research in Photorealistic 3D Simulation and on Real Robots
We introduce BenchBot, a novel software suite for benchmarking the perfo...
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04/06/2020
Class Anchor Clustering: a Distance-based Loss for Training Open Set Classifiers
Existing open set classifiers distinguish between known and unknown inpu...
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03/11/2020
Multiplicative Controller Fusion: A Hybrid Navigation Strategy For Deployment in Unknown Environments
Learning-based approaches often outperform hand-coded algorithmic soluti...
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01/08/2020
What can robotics research learn from computer vision research?
The computer vision and robotics research communities are each strong. H...
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09/24/2019
Residual Reactive Navigation: Combining Classical and Learned Navigation Strategies For Deployment in Unknown Environments
In this work we focus on improving the efficiency and generalisation of ...
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09/16/2019
Where are the Keys? -- Learning Object-Centric Navigation Policies on Semantic Maps with Graph Convolutional Networks
Emerging object-based SLAM algorithms can build a graph representation o...
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03/19/2019
The Probabilistic Object Detection Challenge
We introduce a new challenge for computer and robotic vision, the first ...
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03/15/2019
Did You Miss the Sign? A False Negative Alarm System for Traffic Sign Detectors
Object detection is an integral part of an autonomous vehicle for its sa...
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11/27/2018
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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09/20/2018
Zero-shot Sim-to-Real Transfer with Modular Priors
Current end-to-end Reinforcement Learning (RL) approaches are severely l...
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09/19/2018
An Orientation Factor for Object-Oriented SLAM
Current approaches to object-oriented SLAM lack the ability to incorpora...
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09/17/2018
Evaluating Merging Strategies for Sampling-based Uncertainty Techniques in Object Detection
There has been a recent emergence of sampling-based techniques for estim...
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07/11/2018
Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal
Model-free reinforcement learning has recently been shown to be effectiv...
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04/18/2018
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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04/10/2018
QuadricSLAM: Constrained Dual Quadrics from Object Detections as Landmarks in Semantic SLAM
Research in Simultaneous Localization And Mapping (SLAM) is increasingly...
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11/20/2017
Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments
A robot that can carry out a natural-language instruction has been a dre...
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10/18/2017
Dropout Sampling for Robust Object Detection in Open-Set Conditions
Dropout Variational Inference, or Dropout Sampling, has been recently pr...
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09/21/2017
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes
This paper presents SceneCut, a novel approach to jointly discover previ...
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06/21/2017
Multi-Modal Trip Hazard Affordance Detection On Construction Sites
Trip hazards are a significant contributor to accidents on construction ...
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03/21/2017
Episode-Based Active Learning with Bayesian Neural Networks
We investigate different strategies for active learning with Bayesian de...
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01/18/2017
Deep Learning Features at Scale for Visual Place Recognition
The success of deep learning techniques in the computer vision domain ha...
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01/17/2015
