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A Framework for Collaborative Multi-Robot Mapping using Spectral Graph Wavelets
Lukas Bernreiter, Shehryar Khattak, Lionel Ott +3
The exploration of large-scale unknown environments can benefit from the deployment of multiple robots for collaborative mapping. Each robot explores a section of the environment a…
Unsupervised Continual Semantic Adaptation through Neural Rendering
Zhizheng Liu, Francesco Milano, Jonas Frey +3
An increasing amount of applications rely on data-driven models that are deployed for perception tasks across a sequence of scenes. Due to the mismatch between training and deploym…
SphNet: A Spherical Network for Semantic Pointcloud Segmentation
Lukas Bernreiter, Lionel Ott, Roland Siegwart +1
Semantic segmentation for robotic systems can enable a wide range of applications, from self-driving cars and augmented reality systems to domestic robots. We argue that a spherica…
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…
3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs
Samuel Looper, Javier Rodriguez-Puigvert, Roland Siegwart +2
Numerous applications require robots to operate in environments shared with other agents, such as humans or other robots. However, such shared scenes are typically subject to diffe…
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…