1 citations · 2 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
GFlowVLM: Enhancing Multi-step Reasoning in Vision-Language Models with Generative Flow Networks
Haoqiang Kang, Enna Sachdeva, Piyush Gupta +2
Vision-Language Models (VLMs) have recently shown promising advancements in sequential decision-making tasks through task-specific fine-tuning. However, common fine-tuning methods,…
Graph-Grounded LLMs: Leveraging Graphical Function Calling to Minimize LLM Hallucinations
Piyush Gupta, Sangjae Bae, David Isele
The adoption of Large Language Models (LLMs) is rapidly expanding across various tasks that involve inherent graphical structures. Graphs are integral to a wide range of applicatio…
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…
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…
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…
Optimal Fidelity Selection for Human-Supervised Search
Piyush Gupta, Vaibhav Srivastava
We study optimal fidelity selection in human-supervised underwater visual search, where operator performance is affected by cognitive factors like workload and fatigue. In our expe…
Fostering Human Learning in Sequential Decision-Making: Understanding the Role of Evaluative Feedback
Piyush Gupta, Subir Biswas, Vaibhav Srivastava
Cognitive rehabilitation, STEM (science, technology, engineering, and math) skill acquisition, and coaching games such as chess often require tutoring decision-making strategies. T…