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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

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Showing 2024Show all

6 papers · 1 filter

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…