activity
20202026
most citedConservative Safety Critics for Exploration

32 citations · 162 across the 19 of their papers we have counts for

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12 papers · 1 filter

cs.RO2026

Dynamic Execution Horizon Prediction for Chunk-based Robot Policies

Yuchi Zhao, Miroslav Bogdanovic, Arjun Sohal +5

Action chunking has become a standard design in modern robot policies, from diffusion/flow policies to vision-language-action models, where the policy predicts a sequence of action…

cs.RO2026

Diversity You Can Actually Measure: A Fast, Model-Free Diversity Metric for Robotics Datasets

Sreevardhan Sirigiri, Nathan Samuel de Lara, Christopher Agia +2

Robotics datasets for imitation learning typically consist of long-horizon trajectories of different lengths over states, actions, and high-dimensional observations (e.g., RGB vide…

cs.RO2026★ 6 cited

MATTERIX: toward a digital twin for robotics-assisted chemistry laboratory automation

Kourosh Darvish, Arjun Sohal, Abhijoy Mandal +20

Accelerated materials discovery is critical for addressing global challenges. However, developing new laboratory workflows relies heavily on real-world experimental trials, and thi…

cs.RO2025★ 4 cited

RoboCulture: A Robotics Platform for Automated Biological Experimentation

Kevin Angers, Kourosh Darvish, Naruki Yoshikawa +6

Automating biological experimentation remains challenging due to the need for millimeter-scale precision, long and multi-step experiments, and the dynamic nature of living systems.…

cs.RO2025★ 4 cited

AnyPlace: Learning Generalized Object Placement for Robot Manipulation

Yuchi Zhao, Miroslav Bogdanovic, Chengyuan Luo +5

Object placement in robotic tasks is inherently challenging due to the diversity of object geometries and placement configurations. To address this, we propose AnyPlace, a two-stag…

cs.RO2025★ 2 cited

Accelerating Discovery in Natural Science Laboratories with AI and Robotics: Perspectives and Challenges from the 2024 IEEE ICRA Workshop, Yokohama, Japan

Andrew I. Cooper, Patrick Courtney, Kourosh Darvish +20

Science laboratory automation enables accelerated discovery in life sciences and materials. However, it requires interdisciplinary collaboration to address challenges such as robus…

cs.RO2024★ 22 cited

ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization

Kourosh Darvish, Marta Skreta, Yuchi Zhao +9

Chemistry experiments can be resource- and labor-intensive, often requiring manual tasks like polishing electrodes in electrochemistry. Traditional lab automation infrastructure fa…

cs.RO2023★ 18 cited

Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting

Marta Skreta, Naruki Yoshikawa, Sebastian Arellano-Rubach +6

Generating low-level robot task plans from high-level natural language instructions remains a challenging problem. Although large language models have shown promising results in ge…

cs.RO2023★ 6 cited

MVTrans: Multi-View Perception of Transparent Objects

Yi Ru Wang, Yuchi Zhao, Haoping Xu +4

Transparent object perception is a crucial skill for applications such as robot manipulation in household and laboratory settings. Existing methods utilize RGB-D or stereo inputs t…

cs.RO2022★ 13 cited

Chemistry Lab Automation via Constrained Task and Motion Planning

Naruki Yoshikawa, Andrew Zou Li, Kourosh Darvish +6

Chemists need to perform many laborious and time-consuming experiments in the lab to discover and understand the properties of new materials. To support and accelerate this process…

cs.RO2022★ 2 cited

NeurIPS 2022 Competition: Driving SMARTS

Amir Rasouli, Randy Goebel, Matthew E. Taylor +15

Driving SMARTS is a regular competition designed to tackle problems caused by the distribution shift in dynamic interaction contexts that are prevalent in real-world autonomous dri…

cs.RO2020

LEAF: Latent Exploration Along the Frontier

Homanga Bharadhwaj, Animesh Garg, Florian Shkurti

Self-supervised goal proposal and reaching is a key component for exploration and efficient policy learning algorithms. Such a self-supervised approach without access to any oracle…