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Distant Vehicle Detection Using Radar and Vision

Distant Vehicle Detection Using Radar and Vision Abstract – For autonomous vehicles to be able to operate successfully they need to be aware of other vehicles with sufficient time to make safe, stable plans. Given the possible closing speeds between two vehicles, this necessitates the ability to accurately detect distant vehicles. Many current image-based [...]

By |2020-07-23T10:11:56+01:00July 23rd, 2020|MRG, MRG Highlights, MRG News|Comments Off on Distant Vehicle Detection Using Radar and Vision

Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision

Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision Abstract – Reliable outdoor deployment of mobile robots requires the robust identification of permissible driving routes in a given environment. The performance of LiDAR and vision-based perception systems deteriorates significantly if certain environmental factors are present e.g. rain, fog, darkness. Perception [...]

By |2020-05-11T16:54:01+01:00May 11th, 2020|MRG, MRG Highlights, MRG News|Comments Off on Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision

Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios

Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios Abstract – This paper discusses ongoing work in demonstrating research in mobile autonomy in challenging driving scenarios. In our approach, we address fundamental technical issues to overcome critical barriers to assurance and regulation for large-scale deployments of autonomous systems. To this end, [...]

By |2020-05-26T14:38:48+01:00May 5th, 2020|CRG, MRG, MRG Highlights, MRG News|Comments Off on Sense-Assess-eXplain (SAX): Building Trust in Autonomous Vehicles in Challenging Real-World Driving Scenarios

RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar

RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar Abstract – This paper presents an efficient annotation procedure and an application thereof to end-to-end, rich semantic segmentation of the sensed environment using FMCW scanning radar. We advocate radar over the traditional sensors used for this task as it operates at longer ranges and is substantially more [...]

By |2020-04-07T12:14:04+01:00April 7th, 2020|MRG, MRG Highlights, MRG News|Comments Off on RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar

LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic

LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic This paper presents a system for improving the robustness of LiDAR lateral localisation systems. This is made possible by including detections of road boundaries which are invisible to the sensor (due to occlusion, e.g. traffic) but can be located by our Occluded Road Boundary Inference Deep [...]

By |2020-03-10T17:57:34+00:00March 10th, 2020|MRG, MRG Highlights, MRG News|Comments Off on LiDAR Lateral Localisation Despite Challenging Occlusion from Traffic

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance Abstract - This paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave radar - a commercially promising sensor poised for exploitation in mobile autonomy. We show how a rotationally-invariant metric embedding for radar scans can [...]

By |2020-03-10T17:54:45+00:00March 10th, 2020|MRG, MRG Highlights, MRG News|Comments Off on Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance

Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset

Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset Abstract - We describe the release of reference data towards a challenging long-term localisation and mapping benchmark based on the large-scale Oxford RobotCar Dataset. The release includes 72 traversals of a route through Oxford, UK, gathered in all illumination, weather and traffic conditions, and is [...]

By |2020-02-25T10:31:16+00:00February 25th, 2020|MRG, MRG Highlights, MRG News|Comments Off on Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset

7 years on

Exactly 7 years ago, MRG made the headlines as they demonstrated the first autonomous vehicle on UK roads, driving around Begbroke Science Park on a snowy winters day. Which makes today a great day to celebrate the achievements of this amazing robot.   Since then, the RobotCar has become the most notable data collection platform [...]

By |2020-02-14T16:39:35+00:00February 14th, 2020|MRG News, News Feed, yr_2020|Comments Off on 7 years on

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning Abstract - This paper presents a system for robust, large-scale topological localisation using Frequency-Modulated ContinuousWave (FMCW) scanning radar. We learn a metric space for embedding polar radar scans using CNN and NetVLAD architectures traditionally applied to the visual domain. However, we tailor the feature extraction [...]

By |2020-01-30T12:33:15+00:00January 30th, 2020|MRG, MRG Highlights, MRG News|Comments Off on Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning

I Can See Clearly Now : Image Restoration via De-Raining

This blog post provides an overview of our paper: [bibtex key="ICRA19_porav"] Abstract We present a method for improving segmentation tasks on images affected by adherent rain drops and streaks. We introduce a novel stereo dataset recorded using a system that allows one lens to be affected by real water droplets while keeping the other lens [...]

By |2019-11-22T12:22:23+00:00November 22nd, 2019|MRG, MRG Highlights, MRG News|Comments Off on I Can See Clearly Now : Image Restoration via De-Raining
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