activity
20192025
most citedLearning Agile Robotic Locomotion Skills by Imitating Animals

41 citations · 92 across the 10 of their papers we have counts for

collaborators

14 papers

cs.RO2025★ 1 cited

Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169

General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…

cs.RO2025★ 6 cited

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115

Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…

cs.RO2024★ 2 cited

Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs

Hao-Tien Lewis Chiang, Zhuo Xu, Zipeng Fu +19

An elusive goal in navigation research is to build an intelligent agent that can understand multimodal instructions including natural language and image, and perform useful navigat…

cs.RO2024★ 1 cited

VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration

Michael Ahn, Montserrat Gonzalez Arenas, Matthew Bennice +22

Robots today can exploit the rich world knowledge of large language models to chain simple behavioral skills into long-horizon tasks. However, robots often get interrupted during l…

cs.RO2024★ 5 cited

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Soroush Nasiriany, Fei Xia, Wenhao Yu +20

Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interactio…

cs.RO2024★ 1 cited

Learning to Learn Faster from Human Feedback with Language Model Predictive Control

Jacky Liang, Fei Xia, Wenhao Yu +47

Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…

cs.RO2024★ 14 cited

AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents

Michael Ahn, Debidatta Dwibedi, Chelsea Finn +24

Foundation models that incorporate language, vision, and more recently actions have revolutionized the ability to harness internet scale data to reason about useful tasks. However,…

cs.RO2023★ 16 cited

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms

Anthony Francis, Claudia Pérez-D'Arpino, Chengshu Li +28

A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation ha…

cs.RO2020★ 41 cited

Learning Agile Robotic Locomotion Skills by Imitating Animals

Xue Bin Peng, Erwin Coumans, Tingnan Zhang +3

Reproducing the diverse and agile locomotion skills of animals has been a longstanding challenge in robotics. While manually-designed controllers have been able to emulate many com…

cs.MA2020★ 5 cited

Model-based Reinforcement Learning for Decentralized Multiagent Rendezvous

Rose E. Wang, J. Chase Kew, Dennis Lee +5

Collaboration requires agents to align their goals on the fly. Underlying the human ability to align goals with other agents is their ability to predict the intentions of others an…

cs.RO2019

Learned Critical Probabilistic Roadmaps for Robotic Motion Planning

Brian Ichter, Edward Schmerling, Tsang-Wei Edward Lee +1

Sampling-based motion planning techniques have emerged as an efficient algorithmic paradigm for solving complex motion planning problems. These approaches use a set of probing samp…

cs.RO2019

Neural Collision Clearance Estimator for Batched Motion Planning

J. Chase Kew, Brian Ichter, Maryam Bandari +2

We present a neural network collision checking heuristic, ClearanceNet, and a planning algorithm, CN-RRT. ClearanceNet learns to predict separation distance (minimum distance betwe…

cs.RO2019

Long Range Neural Navigation Policies for the Real World

Ayzaan Wahid, Alexander Toshev, Marek Fiser +1

Learned Neural Network based policies have shown promising results for robot navigation. However, most of these approaches fall short of being used on a real robot due to the exten…

cs.RO2019

Long-Range Indoor Navigation with PRM-RL

Anthony Francis, Aleksandra Faust, Hao-Tien Lewis Chiang +4

Long-range indoor navigation requires guiding robots with noisy sensors and controls through cluttered environments along paths that span a variety of buildings. We achieve this wi…