activity
20202026
most citedRobots That Ask For Help: Uncertainty Alignment for Large Language Model Planners

43 citations · 117 across the 15 of their papers we have counts for

collaborators

16 papers

eess.SY2026

Paying for Space: Incentive-Aware Motion Planning for Multi-Agent Collision Avoidance

Debajyoti Chakrabarti, Anushri Dixit

Advanced Air Mobility (AAM) systems require scalable coordination mechanisms to manage large fleets of aerial vehicles operating in shared, capacity-limited airspace. In such envir…

cs.RO2025★ 10 cited

An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments

Ali Agha, Kyohei Otsu, Benjamin Morrell +86

This paper presents an appendix to the original NeBula autonomy solution developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), participating in the DARPA Sub…

cs.RO2024

Risk-Aware Robotics: Tail Risk Measures in Planning, Control, and Verification

Prithvi Akella, Anushri Dixit, Mohamadreza Ahmadi +5

The need for a systematic approach to risk assessment has increased in recent years due to the ubiquity of autonomous systems that alter our day-to-day experiences and their need f…

cs.RO2023★ 43 cited

Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners

Allen Z. Ren, Anushri Dixit, Alexandra Bodrova +11

Large language models (LLMs) exhibit a wide range of promising capabilities -- from step-by-step planning to commonsense reasoning -- that may provide utility for robots, but remai…

cs.RO2023★ 12 cited

STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation; Results from the DARPA Subterranean Challenge

Anushri Dixit, David D. Fan, Kyohei Otsu +3

Although autonomy has gained widespread usage in structured and controlled environments, robotic autonomy in unknown and off-road terrain remains a difficult problem. Extreme, off-…

cs.RO2022★ 7 cited

Adaptive Conformal Prediction for Motion Planning among Dynamic Agents

Anushri Dixit, Lars Lindemann, Skylar Wei +3

This paper proposes an algorithm for motion planning among dynamic agents using adaptive conformal prediction. We consider a deterministic control system and use trajectory predict…

cs.RO2022

PrePARE: Predictive Proprioception for Agile Failure Event Detection in Robotic Exploration of Extreme Terrains

Sharmita Dey, David Fan, Robin Schmid +5

Legged robots can traverse a wide variety of terrains, some of which may be challenging for wheeled robots, such as stairs or highly uneven surfaces. However, quadruped robots face…

cs.AI2022★ 4 cited

Sample-Based Bounds for Coherent Risk Measures: Applications to Policy Synthesis and Verification

Prithvi Akella, Anushri Dixit, Mohamadreza Ahmadi +2

The dramatic increase of autonomous systems subject to variable environments has given rise to the pressing need to consider risk in both the synthesis and verification of policies…

eess.SY2022★ 8 cited

Risk-Averse Receding Horizon Motion Planning for Obstacle Avoidance using Coherent Risk Measures

Anushri Dixit, Mohamadreza Ahmadi, Joel W. Burdick

This paper studies the problem of risk-averse receding horizon motion planning for agents with uncertain dynamics, in the presence of stochastic, dynamic obstacles. We propose a mo…

cs.RO2022★ 1 cited

Moving Obstacle Avoidance: a Data-Driven Risk-Aware Approach

Skylar X. Wei, Anushri Dixit, Shashank Tomar +1

This paper proposes a new structured method for a moving agent to predict the paths of dynamically moving obstacles and avoid them using a risk-aware model predictive control (MPC)…

eess.SY2022

Distributionally Robust Model Predictive Control with Total Variation Distance

Anushri Dixit, Mohamadreza Ahmadi, Joel W. Burdick

This paper studies the problem of distributionally robust model predictive control (MPC) using total variation distance ambiguity sets. For a discrete-time linear system with addit…

eess.SY2021

Risk-Averse Stochastic Shortest Path Planning

Mohamadreza Ahmadi, Anushri Dixit, Joel W. Burdick +1

We consider the stochastic shortest path planning problem in MDPs, i.e., the problem of designing policies that ensure reaching a goal state from a given initial state with minimum…

cs.RO2021★ 20 cited

NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge

Ali Agha, Kyohei Otsu, Benjamin Morrell +69

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARP…

cs.RO2021★ 11 cited

STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation

David D. Fan, Kyohei Otsu, Yuki Kubo +3

Although ground robotic autonomy has gained widespread usage in structured and controlled environments, autonomy in unknown and off-road terrain remains a difficult problem. Extrem…

eess.SY2020

Risk-Sensitive Motion Planning using Entropic Value-at-Risk

Anushri Dixit, Mohamadreza Ahmadi, Joel W. Burdick

We consider the problem of risk-sensitive motion planning in the presence of randomly moving obstacles. To this end, we adopt a model predictive control (MPC) scheme and pose the o…

cs.RO2020★ 1 cited

The Kinematics of Tracked Vehicles via the Power Dissipation Method

Anushri Dixit, Joel Burdick

This paper develops a new quasi-static modeling framework for tracked robots based on the power dissipation method. Given a set of track speeds, this method predicts the vehicle's…