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20242026
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cs.RO2026

KGLAMP: Knowledge Graph-guided Language model for Adaptive Multi-robot Planning and Replanning

Chak Lam Shek, Faizan M. Tariq, Sangjae Bae +2

Heterogeneous multi-robot systems are increasingly used in long-horizon missions requiring coordinated planning across diverse capabilities. However, existing planning approaches s…

cs.RO2026

Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teams

Piyush Gupta, Sangjae Bae, Jiachen Li +1

Long-horizon task planning for heterogeneous multi-robot systems is essential for deploying collaborative teams in real-world environments; yet, it remains challenging due to the l…

cs.RO2025

IANN-MPPI: Interaction-Aware Neural Network-Enhanced Model Predictive Path Integral Approach for Autonomous Driving

Kanghyun Ryu, Minjun Sung, Piyush Gupta +4

Motion planning for autonomous vehicles (AVs) in dense traffic is challenging, often leading to overly conservative behavior and unmet planning objectives. This challenge stems fro…

cs.RO2025

Generalized Mission Planning for Heterogeneous Multi-Robot Teams via LLM-constructed Hierarchical Trees

Piyush Gupta, David Isele, Enna Sachdeva +4

We present a novel mission-planning strategy for heterogeneous multi-robot teams, taking into account the specific constraints and capabilities of each robot. Our approach employs…

cs.RO2024

Gaussian Lane Keeping: A Robust Prediction Baseline

David Isele, Piyush Gupta, Xinyi Liu +1

Predicting agents' behavior for vehicles and pedestrians is challenging due to a myriad of factors including the uncertainty attached to different intentions, inter-agent interacti…

cs.RO2024

Towards Scalable & Efficient Interaction-Aware Planning in Autonomous Vehicles using Knowledge Distillation

Piyush Gupta, David Isele, Sangjae Bae

Real-world driving involves intricate interactions among vehicles navigating through dense traffic scenarios. Recent research focuses on enhancing the interaction awareness of auto…