209 citations · 741 across the 33 of their papers we have counts for
7 papers · 2 filters
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning
Le Chen, Yunke Ao, Florian Tschopp +5
Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of…
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…
A Unified Approach for Autonomous Volumetric Exploration of Large Scale Environments under Severe Odometry Drift
Lukas Schmid, Victor Reijgwart, Lionel Ott +3
Exploration is a fundamental problem in robot autonomy. A major limitation, however, is that during exploration robots oftentimes have to rely on on-board systems alone for state e…
Precise Robot Localization in Architectural 3D Plans
Hermann Blum, Julian Stiefel, Cesar Cadena +2
This paper presents a localization system for mobile robots enabling precise localization in inaccurate building models. The approach leverages local referencing to counteract inhe…
Learning Camera Miscalibration Detection
Andrei Cramariuc, Aleksandar Petrov, Rohit Suri +3
Self-diagnosis and self-repair are some of the key challenges in deploying robotic platforms for long-term real-world applications. One of the issues that can occur to a robot is m…
Voxgraph: Globally Consistent, Volumetric Mapping using Signed Distance Function Submaps
Victor Reijgwart, Alexander Millane, Helen Oleynikova +3
Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and…