activity
20202026
most citedWelfare Maximization Algorithm for Solving Budget-Constrained Multi-Component POMDPs

4 citations · 6 across the 12 of their papers we have counts for

collaborators

14 papers

cs.RO2026

Whole-Body Dexterity

Conor Mc Gartoll, An Dang, Pranay Thangeda +5

Current humanoid dexterous manipulation remains largely confined to end-effectors and simple grasps, falling short of humans' ability to engage the entire body by bracing and slidi…

cs.RO2026

Trajectory-Level Redirection Attacks on Vision-Language-Action Models

Gokul Puthumanaillam, Vardhan Dongre, Pranay Thangeda +3

Vision-language-action (VLA) policies bring natural language into closed-loop robot control, enabling robots to execute manipulation tasks directly from text instructions. The same…

cs.RO2025

TRACE: A Self-Improving Framework for Robot Behavior Forecasting with Vision-Language Models

Gokul Puthumanaillam, Paulo Padrao, Jose Fuentes +6

Predicting the near-term behavior of a reactive agent is crucial in many robotic scenarios, yet remains challenging when observations of that agent are sparse or intermittent. Visi…

cs.RO2024

Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control

Noah Franceschini, Pranay Thangeda, Melkior Ornik +1

This paper addresses the challenge of autonomous excavation of challenging terrains, in particular those that are prone to jamming and inter-particle adhesion when tackled by a sta…

cs.AI2024

InfraLib: Enabling Reinforcement Learning and Decision-Making for Large-Scale Infrastructure Management

Pranay Thangeda, Trevor S. Betz, Michael N. Grussing +1

Efficient management of infrastructure systems is crucial for economic stability, sustainability, and public safety. However, infrastructure sustainment is challenging due to the v…

cs.RO2024

Learning to Turn: Diffusion Imitation for Robust Row Turning in Under-Canopy Robots

Arun N. Sivakumar, Pranay Thangeda, Yixiao Fang +4

Under-canopy agricultural robots require robust navigation capabilities to enable full autonomy but struggle with tight row turning between crop rows due to degraded GPS reception,…

cs.RO2024

Few-shot Scooping Under Domain Shift via Simulated Maximal Deployment Gaps

Yifan Zhu, Pranay Thangeda, Erica L Tevere +5

Autonomous lander missions on extraterrestrial bodies need to sample granular materials while coping with domain shifts, even when sampling strategies are extensively tuned on Eart…

cs.AI2024

Optimizing Agricultural Order Fulfillment Systems: A Hybrid Tree Search Approach

Pranay Thangeda, Hoda Helmi, Melkior Ornik

Efficient order fulfillment is vital in the agricultural industry, particularly due to the seasonal nature of seed supply chains. This paper addresses the challenge of optimizing s…

cs.CY2024★ 1 cited

A Moral Imperative: The Need for Continual Superalignment of Large Language Models

Gokul Puthumanaillam, Manav Vora, Pranay Thangeda +1

This paper examines the challenges associated with achieving life-long superalignment in AI systems, particularly large language models (LLMs). Superalignment is a theoretical fram…

cs.RO2023

Learning and Autonomy for Extraterrestrial Terrain Sampling: An Experience Report from OWLAT Deployment

Pranay Thangeda, Ashish Goel, Erica Tevere +6

Extraterrestrial autonomous lander missions increasingly demand adaptive capabilities to handle the unpredictable and diverse nature of the terrain. This paper discusses the deploy…

math.OC2023★ 4 cited

Welfare Maximization Algorithm for Solving Budget-Constrained Multi-Component POMDPs

Manav Vora, Pranay Thangeda, Michael N. Grussing +1

Partially Observable Markov Decision Processes (POMDPs) provide an efficient way to model real-world sequential decision making processes. Motivated by the problem of maintenance a…

cs.RO2023

Few-shot Adaptation for Manipulating Granular Materials Under Domain Shift

Yifan Zhu, Pranay Thangeda, Melkior Ornik +1

Autonomous lander missions on extraterrestrial bodies will need to sample granular material while coping with domain shift, no matter how well a sampling strategy is tuned on Earth…

cs.AI2021★ 1 cited

Efficient Strategy Synthesis for MDPs with Resource Constraints

František Blahoudek, Petr Novotný, Melkior Ornik +2

We consider qualitative strategy synthesis for the formalism called consumption Markov decision processes. This formalism can model dynamics of an agents that operates under resour…

cs.FL2020

Qualitative Controller Synthesis for Consumption Markov Decision Processes

František Blahoudek, Tomáš Brázdil, Petr Novotný +3

Consumption Markov Decision Processes (CMDPs) are probabilistic decision-making models of resource-constrained systems. In a CMDP, the controller possesses a certain amount of a cr…