1.1k citations · 2.2k across the 12 of their papers we have counts for
13 papers
Learning Robust Autonomous Navigation and Locomotion for Wheeled-Legged Robots
Joonho Lee, Marko Bjelonic, Alexander Reske +3
Autonomous wheeled-legged robots have the potential to transform logistics systems, improving operational efficiency and adaptability in urban environments. Navigating urban enviro…
Learning to walk in confined spaces using 3D representation
Takahiro Miki, Joonho Lee, Lorenz Wellhausen +1
Legged robots have the potential to traverse complex terrain and access confined spaces beyond the reach of traditional platforms thanks to their ability to carefully select footho…
ArtPlanner: Robust Legged Robot Navigation in the Field
Lorenz Wellhausen, Marco Hutter
Due to the highly complex environment present during the DARPA Subterranean Challenge, all six funded teams relied on legged robots as part of their robotic team. Their unique loco…
Self-Supervised Traversability Prediction by Learning to Reconstruct Safe Terrain
Robin Schmid, Deegan Atha, Frederik Schöller +8
Navigating off-road with a fast autonomous vehicle depends on a robust perception system that differentiates traversable from non-traversable terrain. Typically, this depends on a…
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…
Elevation Mapping for Locomotion and Navigation using GPU
Takahiro Miki, Lorenz Wellhausen, Ruben Grandia +3
Perceiving the surrounding environment is crucial for autonomous mobile robots. An elevation map provides a memory-efficient and simple yet powerful geometric representation for gr…
Learning robust perceptive locomotion for quadrupedal robots in the wild
Takahiro Miki, Joonho Lee, Jemin Hwangbo +3
Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into under-explored areas. Exteroceptive percep…
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…
Deep Measurement Updates for Bayes Filters
Johannes Pankert, Maria Vittoria Minniti, Lorenz Wellhausen +1
Measurement update rules for Bayes filters often contain hand-crafted heuristics to compute observation probabilities for high-dimensional sensor data, like images. In this work, w…
Learning a State Representation and Navigation in Cluttered and Dynamic Environments
David Hoeller, Lorenz Wellhausen, Farbod Farshidian +1
In this work, we present a learning-based pipeline to realise local navigation with a quadrupedal robot in cluttered environments with static and dynamic obstacles. Given high-leve…
Learning Quadrupedal Locomotion over Challenging Terrain
Joonho Lee, Jemin Hwangbo, Lorenz Wellhausen +2
Some of the most challenging environments on our planet are accessible to quadrupedal animals but remain out of reach for autonomous machines. Legged locomotion can dramatically ex…
Safe Robot Navigation via Multi-Modal Anomaly Detection
Lorenz Wellhausen, René Ranftl, Marco Hutter
Navigation in natural outdoor environments requires a robust and reliable traversability classification method to handle the plethora of situations a robot can encounter. Binary cl…
Walking Posture Adaptation for Legged Robot Navigation in Confined Spaces
Russell Buchanan, Tirthankar Bandyopadhyay, Marko Bjelonic +3
Legged robots have the ability to adapt their walking posture to navigate confined spaces due to their high degrees of freedom. However, this has not been exploited in most common…