activity
20232026
most citedLearning Agile Locomotion on Risky Terrains

2 citations · 9 across the 11 of their papers we have counts for

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12 papers · 1 filter

cs.RO2026

Large-Scale Autonomous Gas Monitoring for Volcanic Environments: A Legged Robot on Mount Etna

Julia Richter, Turcan Tuna, Manthan Patel +6

Volcanic gas emissions are key precursors of eruptive activity. Yet, obtaining accurate near-surface measurements remains hazardous and logistically challenging, motivating the nee…

cs.RO2025

DAPPER: Discriminability-Aware Policy-to-Policy Preference-Based Reinforcement Learning for Query-Efficient Robot Skill Acquisition

Yuki Kadokawa, Jonas Frey, Takahiro Miki +2

Preference-based Reinforcement Learning (PbRL) enables policy learning through simple queries comparing trajectories from a single policy. While human responses to these queries ma…

cs.RO2024★ 1 cited

RoadRunner M&M -- Learning Multi-range Multi-resolution Traversability Maps for Autonomous Off-road Navigation

Manthan Patel, Jonas Frey, Deegan Atha +3

Autonomous robot navigation in off-road environments requires a comprehensive understanding of the terrain geometry and traversability. The degraded perceptual conditions and spars…

cs.RO2024★ 2 cited

Learning to Open and Traverse Doors with a Legged Manipulator

Mike Zhang, Yuntao Ma, Takahiro Miki +1

Using doors is a longstanding challenge in robotics and is of significant practical interest in giving robots greater access to human-centric spaces. The task is challenging due to…

cs.RO2024

Identifying Terrain Physical Parameters from Vision -- Towards Physical-Parameter-Aware Locomotion and Navigation

Jiaqi Chen, Jonas Frey, Ruyi Zhou +3

Identifying the physical properties of the surrounding environment is essential for robotic locomotion and navigation to deal with non-geometric hazards, such as slippery and defor…

cs.RO2024

Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllers

Fan Shi, Chong Zhang, Takahiro Miki +3

Legged locomotion has recently achieved remarkable success with the progress of machine learning techniques, especially deep reinforcement learning (RL). Controllers employing neur…

cs.RO2024★ 2 cited

Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment

Matías Mattamala, Nived Chebrolu, Benoit Casseau +5

We present a solution for autonomous forest inventory with a legged robotic platform. Compared to their wheeled and aerial counterparts, legged platforms offer an attractive balanc…

cs.RO2024★ 1 cited

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…

cs.RO2023★ 2 cited

Learning Agile Locomotion on Risky Terrains

Chong Zhang, Nikita Rudin, David Hoeller +1

Quadruped robots have shown remarkable mobility on various terrains through reinforcement learning. Yet, in the presence of sparse footholds and risky terrains such as stepping sto…

cs.RO2023

Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End

Jin Jin, Chong Zhang, Jonas Frey +4

Autonomous robots must navigate reliably in unknown environments even under compromised exteroceptive perception, or perception failures. Such failures often occur when harsh envir…

cs.RO2023★ 1 cited

MEM: Multi-Modal Elevation Mapping for Robotics and Learning

Gian Erni, Jonas Frey, Takahiro Miki +2

Elevation maps are commonly used to represent the environment of mobile robots and are instrumental for locomotion and navigation tasks. However, pure geometric information is insu…

cs.RO2023

Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning

Lukas Schneider, Jonas Frey, Takahiro Miki +1

Deployment in hazardous environments requires robots to understand the risks associated with their actions and movements to prevent accidents. Despite its importance, these risks a…