4.2k citations · 4.4k across the 40 of their papers we have counts for
6 papers · 2 filters
Learning to Navigate by Growing Deep Networks
Thushan Ganegedara, Lionel Ott, Fabio Ramos
Adaptability is central to autonomy. Intuitively, for high-dimensional learning problems such as navigating based on vision, internal models with higher complexity allow to accurat…
Bayesian Optimisation for Safe Navigation under Localisation Uncertainty
Rafael Oliveira, Lionel Ott, Vitor Guizilini +1
In outdoor environments, mobile robots are required to navigate through terrain with varying characteristics, some of which might significantly affect the integrity of the platform…
Stochastic Functional Gradient Path Planning in Occupancy Maps
Gilad Francis, Lionel Ott, Fabio Ramos
Planning safe paths is a major building block in robot autonomy. It has been an active field of research for several decades, with a plethora of planning methods. Planners can be g…
Sequential Bayesian Optimisation as a POMDP for Environment Monitoring with UAVs
Philippe Morere, Roman Marchant, Fabio Ramos
Bayesian Optimisation has gained much popularity lately, as a global optimisation technique for functions that are expensive to evaluate or unknown a priori. While classical BO foc…
Occupancy Map Building through Bayesian Exploration
Gilad Francis, Lionel Ott, Roman Marchant +1
We propose a novel holistic approach for safe autonomous exploration and map building based on constrained Bayesian optimisation. This method finds optimal continuous paths instead…
Stochastic Functional Gradient for Motion Planning in Continuous Occupancy Maps
Gilad Francis, Lionel Ott, Fabio Ramos
Safe path planning is a crucial component in autonomous robotics. The many approaches to find a collision free path can be categorically divided into trajectory optimisers and samp…