Actively Mapping Industrial Structures In the context of robotics, active perceptual planning refers to exploration by a mobile robot equipped with sensors to conduct a survey of an object or environment of interest. It can be of assistance for the regular inspection and monitoring of remote or dangerous facilities such as offshore platforms. Active mapping [...]
Visual-Inertial-Kinematic Odometry for Legged Robots (VILENS) This blog post provides an overview of our recent ICRA 2020 paper Preintegrated Velocity Bias Estimation to Overcome Contact Nonlinearities in Legged Robot Odometry: [bibtex key="2020ICRA_wisth"] This is one paper in a series of works on state estimation described here. Introduction Many [...]
Planning for Multiple Robots in Congested Environments When most of us plan journeys, chances are at some point we open Google Maps to find an array of colours telling us that we will probably experience traffic at certain points on our journey. This allows us to plan our [...]
Advanced BIT* (ABIT*): Sampling-Based Planning with Advanced Graph-Search Techniques Path planning is the problem of finding a continuous sequence of valid states from a start to a goal specification. Popular approaches in robotics include graph-based searches, such as A* [1], and sampling-based planners, such as Rapidly-exploring Random Trees (RRT) [2]. Both graph- and sampling-based approaches [...]
Learning from demonstration and reinforcement learning have been applied to many difficult problems in sequential decision making and control. In most settings, it is assumed that the demonstrations available are fixed. In this work, we consider learning from demonstration in the context of shared autonomy...
Our new all-weather platform pictured outside Blenheim Palace. For more information please take a look at the paper as well as the presentation. This blog post provides an overview of our paper which was recently presented by Stephen Kyberd at the 12th Conference on Field and Service Robotics, Tokyo, Japan – “The Hulk: [...]
How do we know when we don’t know? This is an important question to answer in any situation where we need to navigate through our surroundings, and something any autonomous mobile robot needs to know too. We discuss this introspection capability and its importance to our radar-based navigation algorithms [...]
Fast Radar Motion Estimation This blog post provides an overview of our paper “Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision” by Roberto Aldera, Daniele De Martini, Matthew Gadd, and Paul Newman which was recently accepted for publication at the IEEE International Conference on [...]
Over the past few months, one of our 2nd year DPhil students, Mark Finean, has been volunteering as a robotics mentor to a group of girls pursuing their A levels at St Paul’s Girls’ School (SPGS) in London. For a school project, they wished to learn more about robots and investigate how they could [...]
TLDR: Physical intuition is a human super-power. It enables our superior object manipulation skills which we apply in countless scenarios - from playing with toys to using tools. The ShapeStacks project aims to equip robots with a similar intuition by providing a virtual playground in which robots can acquire [...]
