Search Results for author: Helen Oleynikova

Found 6 papers, 4 papers with code

Spatial Computing and Intuitive Interaction: Bringing Mixed Reality and Robotics Together

no code implementations3 Feb 2022 Jeffrey Delmerico, Roi Poranne, Federica Bogo, Helen Oleynikova, Eric Vollenweider, Stelian Coros, Juan Nieto, Marc Pollefeys

Spatial computing -- the ability of devices to be aware of their surroundings and to represent this digitally -- offers novel capabilities in human-robot interaction.

Mixed Reality

Freetures: Localization in Signed Distance Function Maps

no code implementations19 Oct 2020 Alexander Millane, Helen Oleynikova, Christian Lanegger, Jeff Delmerico, Juan Nieto, Roland Siegwart, Marc Pollefeys, Cesar Cadena

Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps.

Robotics

Sparse 3D Topological Graphs for Micro-Aerial Vehicle Planning

2 code implementations12 Mar 2018 Helen Oleynikova, Zachary Taylor, Roland Siegwart, Juan Nieto

Micro-Aerial Vehicles (MAVs) have the advantage of moving freely in 3D space.

Robotics

C-blox: A Scalable and Consistent TSDF-based Dense Mapping Approach

1 code implementation19 Oct 2017 Alexander Millane, Zachary Taylor, Helen Oleynikova, Juan Nieto, Roland Siegwart, César Cadena

Central to our approach is the representation of the environment as a collection of overlapping TSDF subvolumes.

Robotics

Safe Local Exploration for Replanning in Cluttered Unknown Environments for Micro-Aerial Vehicles

2 code implementations2 Oct 2017 Helen Oleynikova, Zachary Taylor, Roland Siegwart, Juan Nieto

We perform extensive simulations to show that this system performs better than the standard approach of using an optimistic global planner, and also outperforms doing a single exploration step when the local planner is stuck.

Robotics

Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-Board MAV Planning

3 code implementations11 Nov 2016 Helen Oleynikova, Zachary Taylor, Marius Fehr, Juan Nieto, Roland Siegwart

We show that we can build TSDFs faster than Octomaps, and that it is more accurate to build ESDFs out of TSDFs than occupancy maps.

Robotics

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