5 citations · 16 across the 5 of their papers we have counts for
6 papers · 1 filter
OCTNet: Trajectory Generation in New Environments from Past Experiences
Weiming Zhi, Tin Lai, Lionel Ott +2
Being able to safely operate for extended periods of time in dynamic environments is a critical capability for autonomous systems. This generally involves the prediction and unders…
Bayesian Local Sampling-based Planning
Tin Lai, Philippe Morere, Fabio Ramos +1
Sampling-based planning is the predominant paradigm for motion planning in robotics. Most sampling-based planners use a global random sampling scheme to guarantee probabilistic com…
Functional Path Optimisation for Exploration in Continuous Occupancy Maps
Gilad Francis, Lionel Ott, Fabio Ramos
Autonomous exploration is a complex task where the robot moves through an unknown environment with the goal of mapping it. The desired output of such a process is a sequence of pat…
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…
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…