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Simon Boche

8 accepted papers

2026

FindAnything: Open-Vocabulary and Object-Centric Mapping for Robot Exploration in Any Environment

Sebastián Barbas Laina, Simon Boche, Sotiris Papatheodorou, Simon Schaefer, Jaehyung Jung, Helen Oleynikova +1
ICRA 2026poster

Geometrically accurate and semantically expressive map representations have proven invaluable for robot deployment and task planning in unknown environments. Nevertheless, real-time, open-vocabulary semantic understanding of large-scale unknown environments still presents open challenges, mainly due…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2026

OKVIS2-X: Open Keyframe-Based Visual-Inertial SLAM Configurable with Dense Depth or LiDAR, and GNSS

Simon Boche, Jaehyung Jung, Sebastián Barbas Laina, Stefan Leutenegger
ICRA 2026poster

To empower mobile robots with usable maps as well as highest state estimation accuracy and robustness, we present OKVIS2-X: a state-of-the-art multi-sensor Simultaneous Localization and Mapping (SLAM) system building dense volumetric occupancy maps, while scalable to large environments and operating…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Efficient Submap-based Autonomous MAV Exploration using Visual-Inertial SLAM Configurable for LiDARs or Depth Cameras

Sotiris Papatheodorou, Simon Boche, Sebastián Barbas Laina, Stefan Leutenegger
ICRA 2025

Autonomous exploration of unknown space is an essential component for the deployment of mobile robots in the real world. Safe navigation is crucial for all robotics applications and requires accurate and consistent maps of the robot's surroundings. To achieve full autonomy and allow deployment in a

Cited by 6Source ↗Scholar ↗
2025

REGRACE: A Robust and Efficient Graph-based Re-localization Algorithm using Consistency Evaluation

Débora N. P. Oliveira, Joshua Knights, Sebastián Barbas Laina, Simon Boche, Wolfram Burgard, Stefan Leutenegger
IROS 2025

Loop closures are essential for correcting odometry drift and creating consistent maps, especially in the context of large-scale navigation. Current methods using dense point clouds for accurate place recognition do not scale well due to computationally expensive scan-to-scan comparisons. Alternativ

Cited by 1Source ↗Scholar ↗
2025

Scalable Outdoors Autonomous Drone Flight with Visual-Inertial SLAM and Dense Submaps Built without LiDAR

Sebastián Barbas Laina, Simon Boche, Sotiris Papatheodorou, Dimos Tzoumanikas, Simon Schaefer, Hanzhi Chen +1
IROS 2025

Autonomous navigation is needed for several robotics applications. In this paper we present an autonomous Micro Aerial Vehicle (MAV) system which purely relies on cost-effective and light-weight passive visual and inertial sensors to perform large-scale autonomous navigation in outdoor, unstructured

Cited by 3Source ↗code ↗Scholar ↗
2025

Uncertainty-Aware Visual-Inertial SLAM with Volumetric Occupancy Mapping

Jaehyung Jung, Simon Boche, Sebastián Barbas Laina, Stefan Leutenegger
ICRA 2025

We propose visual-inertial simultaneous localization and mapping that tightly couples sparse reprojection errors, inertial measurement unit pre-integrals, and relative pose factors with dense volumetric occupancy mapping. Hereby depth predictions from a deep neural network are fused in a fully proba

Cited by 5Source ↗Scholar ↗
2024

Tightly-Coupled LiDAR-Visual-Inertial SLAM and Large-Scale Volumetric Occupancy Mapping

Simon Boche, Sebastián Barbas Laina, Stefan Leutenegger
ICRA 2024poster

Autonomous navigation is one of the key requirements for every potential application of mobile robots in the real-world. Besides high-accuracy state estimation, a suitable and globally consistent representation of the 3D environment is indispensable. We present a fully tightly-coupled LiDAR-Visual-I…

Cited by 8Source ↗Scholar ↗
2022

Visual-Inertial SLAM with Tightly-Coupled Dropout-Tolerant GPS Fusion

Simon Boche, Xingxing Zuo, Simon Schaefer, Stefan Leutenegger
IROS 2022poster

Robotic applications are continuously striving towards higher levels of autonomy. To achieve that goal, a highly robust and accurate state estimation is indispensable. Combining visual and inertial sensor modalities has proven to yield accurate and locally consistent results in short-term applicatio…

Cited by 20Source ↗Scholar ↗