342 citations · 578 across the 39 of their papers we have counts for
15 papers · 1 filter
Beyond Visual Quality: A Study of Test-Time Planning with World Action Models
Jianhao Yuan, Yu Yuan, Benjamin Ramtoula +5
World action models generate actions together with visual predictions of their consequences. These paired outputs create the potential for planning by sampling multiple actions fro…
Risk-Aware Reinforcement Learning for Mobile Manipulation
Michael Groom, James Wilson, Nick Hawes +1
For robots to successfully transition from lab settings to everyday environments, they must begin to reason about the risks associated with their actions and make informed, risk-aw…
GraphSCENE: On-Demand Critical Scenario Generation for Autonomous Vehicles in Simulation
Efimia Panagiotaki, Georgi Pramatarov, Lars Kunze +1
Testing and validating Autonomous Vehicle (AV) performance in safety-critical and diverse scenarios is crucial before real-world deployment. However, manually creating such scenari…
NAR-*ICP: Neural Execution of Classical ICP-based Pointcloud Registration Algorithms
Efimia Panagiotaki, Daniele De Martini, Lars Kunze +2
This study explores the intersection of neural networks and classical robotics algorithms through the Neural Algorithmic Reasoning (NAR) blueprint, enabling the training of neural…
S-RAF: A Simulation-Based Robustness Assessment Framework for Responsible Autonomous Driving
Daniel Omeiza, Pratik Somaiya, Jo-Ann Pattinson +4
As artificial intelligence (AI) technology advances, ensuring the robustness and safety of AI-driven systems has become paramount. However, varying perceptions of robustness among…
Risk-aware Trajectory Prediction by Incorporating Spatio-temporal Traffic Interaction Analysis
Divya Thuremella, Lewis Ince, Lars Kunze
To operate in open-ended environments where humans interact in complex, diverse ways, autonomous robots must learn to predict their behaviour, especially when that behavior is pote…
RobotCycle: Assessing Cycling Safety in Urban Environments
Efimia Panagiotaki, Tyler Reinmund, Stephan Mouton +9
This paper introduces RobotCycle, a novel ongoing project that leverages Autonomous Vehicle (AV) research to investigate how road infrastructure influences cyclist behaviour and sa…
COBRA-PPM: A Causal Bayesian Reasoning Architecture Using Probabilistic Programming for Robot Manipulation Under Uncertainty
Ricardo Cannizzaro, Michael Groom, Jonathan Routley +2
Manipulation tasks require robots to reason about cause and effect when interacting with objects. Yet, many data-driven approaches lack causal semantics and thus only consider corr…
Real-time 3D semantic occupancy prediction for autonomous vehicles using memory-efficient sparse convolution
Samuel Sze, Lars Kunze
In autonomous vehicles, understanding the surrounding 3D environment of the ego vehicle in real-time is essential. A compact way to represent scenes while encoding geometric distan…
OORD: The Oxford Offroad Radar Dataset
Matthew Gadd, Daniele De Martini, Oliver Bartlett +11
There is a growing academic interest as well as commercial exploitation of millimetre-wave scanning radar for autonomous vehicle localisation and scene understanding. Although seve…
RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model
Jianhao Yuan, Shuyang Sun, Daniel Omeiza +4
We need to trust robots that use often opaque AI methods. They need to explain themselves to us, and we need to trust their explanation. In this regard, explainability plays a crit…
Towards Probabilistic Causal Discovery, Inference & Explanations for Autonomous Drones in Mine Surveying Tasks
Ricardo Cannizzaro, Rhys Howard, Paulina Lewinska +1
Causal modelling offers great potential to provide autonomous agents the ability to understand the data-generation process that governs their interactions with the world. Such mode…
Effects of Explanation Specificity on Passengers in Autonomous Driving
Daniel Omeiza, Raunak Bhattacharyya, Nick Hawes +2
The nature of explanations provided by an explainable AI algorithm has been a topic of interest in the explainable AI and human-computer interaction community. In this paper, we in…
Simulation-Based Counterfactual Causal Discovery on Real World Driver Behaviour
Rhys Howard, Lars Kunze
Being able to reason about how one's behaviour can affect the behaviour of others is a core skill required of intelligent driving agents. Despite this, the state of the art struggl…
The STRANDS Project: Long-Term Autonomy in Everyday Environments
Nick Hawes, Chris Burbridge, Ferdian Jovan +30
Thanks to the efforts of the robotics and autonomous systems community, robots are becoming ever more capable. There is also an increasing demand from end-users for autonomous serv…