3 citations · 3 across the 1 of their papers we have counts for
5 papers · 1 filter
Sampling-free obstacle gradients and reactive planning in Neural Radiance Fields (NeRF)
Michael Pantic, Cesar Cadena, Roland Siegwart +1
This work investigates the use of Neural implicit representations, specifically Neural Radiance Fields (NeRF), for geometrical queries and motion planning. We show that by adding t…
Mesh Manifold based Riemannian Motion Planning for Omnidirectional Micro Aerial Vehicles
Michael Pantic, Lionel Ott, Cesar Cadena +2
This paper presents a novel on-line path planning method that enables aerial robots to interact with surfaces. We present a solution to the problem of finding trajectories that dri…
Active Interaction Force Control for Contact-Based Inspection with a Fully Actuated Aerial Vehicle
Karen Bodie, Maximilian Brunner, Michael Pantic +5
This paper presents and validates active interaction force control and planning for fully actuated and omnidirectional aerial manipulation platforms, with the goal of aerial contac…
An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments
Lukas Schmid, Michael Pantic, Raghav Khanna +3
The ability to plan informative paths online is essential to robot autonomy. In particular, sampling-based approaches are often used as they are capable of using arbitrary informat…
An Omnidirectional Aerial Manipulation Platform for Contact-Based Inspection
Karen Bodie, Maximilian Brunner, Michael Pantic +5
This paper presents an omnidirectional aerial manipulation platform for robust and responsive interaction with unstructured environments, toward the goal of contact-based inspectio…