activity
20162026
most citedFast, Autonomous Flight in GPS-Denied and Cluttered Environments

202 citations · 377 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

HIGS: Hierarchical Implicit Grids for Joint Geometric and Semantic Scene Understanding

Hanwen Cao, Wenqiang Wu, Kuang-Ting Tu +5

Neural implicit representations have had a significant impact on scene reconstruction by enabling robots to build continuous, differentiable, and high-fidelity 3D maps. Most existi…

cs.RO2022★ 68 cited

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

Jeffrey Delmerico, Roi Poranne, Federica Bogo +5

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

cs.RO2021★ 71 cited

Panoptic Multi-TSDFs: a Flexible Representation for Online Multi-resolution Volumetric Mapping and Long-term Dynamic Scene Consistency

Lukas Schmid, Jeffrey Delmerico, Johannes Schönberger +4

For robotic interaction in environments shared with other agents, access to volumetric and semantic maps of the scene is crucial. However, such environments are inevitably subject…

cs.RO2020

Freetures: Localization in Signed Distance Function Maps

Alexander Millane, Helen Oleynikova, Christian Lanegger +5

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

cs.RO2017★ 202 cited

Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

Kartik Mohta, Michael Watterson, Yash Mulgaonkar +14

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little…

cs.RO2016★ 36 cited

Perception-aware Path Planning

Gabriele Costante, Christian Forster, Jeffrey Delmerico +2

In this paper, we give a double twist to the problem of planning under uncertainty. State-of-the-art planners seek to minimize the localization uncertainty by only considering the…