100 citations · 327 across the 14 of their papers we have counts for
17 papers
Efficient Hierarchical Any-Angle Path Planning on Multi-Resolution 3D Grids
Victor Reijgwart, Cesar Cadena, Roland Siegwart +1
Hierarchical, multi-resolution volumetric mapping approaches are widely used to represent large and complex environments as they can efficiently capture their occupancy and connect…
Obstacle-Avoidant Leader Following with a Quadruped Robot
Carmen Scheidemann, Lennart Werner, Victor Reijgwart +5
Personal mobile robotic assistants are expected to find wide applications in industry and healthcare. For example, people with limited mobility can benefit from robots helping with…
Framework for Robust Localization of UUVs and Mapping of Net Pens
David Botta, Luca Ebner, Andrej Studer +3
This paper presents a general framework integrating vision and acoustic sensor data to enhance localization and mapping in highly dynamic and complex underwater environments, with…
Waverider: Leveraging Hierarchical, Multi-Resolution Maps for Efficient and Reactive Obstacle Avoidance
Victor Reijgwart, Michael Pantic, Roland Siegwart +1
Fast and reliable obstacle avoidance is an important task for mobile robots. In this work, we propose an efficient reactive system that provides high-quality obstacle avoidance whi…
Efficient volumetric mapping of multi-scale environments using wavelet-based compression
Victor Reijgwart, Cesar Cadena, Roland Siegwart +1
Volumetric maps are widely used in robotics due to their desirable properties in applications such as path planning, exploration, and manipulation. Constant advances in mapping tec…
maplab 2.0 -- A Modular and Multi-Modal Mapping Framework
Andrei Cramariuc, Lukas Bernreiter, Florian Tschopp +5
Integration of multiple sensor modalities and deep learning into Simultaneous Localization And Mapping (SLAM) systems are areas of significant interest in current research. Multi-m…
SC-Explorer: Incremental 3D Scene Completion for Safe and Efficient Exploration Mapping and Planning
Lukas Schmid, Mansoor Nasir Cheema, Victor Reijgwart +3
Exploration of unknown environments is a fundamental problem in robotics and an essential component in numerous applications of autonomous systems. A major challenge in exploring u…
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto, Mihir Dharmadhikari, Lukas Bernreiter +33
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with…
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto, Frank Mascarich, Lukas Bernreiter +38
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy h…
Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots
Mihir Kulkarni, Mihir Dharmadhikari, Marco Tranzatto +10
This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings,…
Dynamic Object Aware LiDAR SLAM based on Automatic Generation of Training Data
Patrick Pfreundschuh, Hubertus Franciscus Cornelis Hendrikx, Victor Reijgwart +3
Highly dynamic environments, with moving objects such as cars or humans, can pose a performance challenge for LiDAR SLAM systems that assume largely static scenes. To overcome this…
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…
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…
End-to-End Velocity Estimation For Autonomous Racing
Sirish Srinivasan, Inkyu Sa, Alex Zyner +3
Velocity estimation plays a central role in driverless vehicles, but standard and affordable methods struggle to cope with extreme scenarios like aggressive maneuvers due to the pr…
Accurate Mapping and Planning for Autonomous Racing
Leiv Andresen, Adrian Brandemuehl, Alex Hönger +11
This paper presents the perception, mapping, and planning pipeline implemented on an autonomous race car. It was developed by the 2019 AMZ driverless team for the Formula Student G…
AMZ Driverless: The Full Autonomous Racing System
Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart +19
This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and…
Design of an Autonomous Racecar: Perception, State Estimation and System Integration
Miguel de la Iglesia Valls, Hubertus Franciscus Cornelis Hendrikx, Victor Reijgwart +6
This paper introduces flüela driverless: the first autonomous racecar to win a Formula Student Driverless competition. In this competition, among other challenges, an autonomous ra…