1 citations · 2 across the 28 of their papers we have counts for
10 papers · 1 filter
Occupancy-aware Trajectory Planning for Autonomous Valet Parking in Uncertain Dynamic Environments
Farhad Nawaz, Faizan M. Tariq, Sangjae Bae +5
Autonomous Valet Parking (AVP) requires planning under partial observability, where parking spot availability evolves as dynamic agents enter and exit spots. Existing approaches ei…
Active Probing with Multimodal Predictions for Motion Planning
Darshan Gadginmath, Farhad Nawaz, Minjun Sung +5
Navigation in dynamic environments requires autonomous systems to reason about uncertainties in the behavior of other agents. In this paper, we introduce a unified framework that c…
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…
Graph-based Path Planning with Dynamic Obstacle Avoidance for Autonomous Parking
Farhad Nawaz, Minjun Sung, Darshan Gadginmath +6
Safe and efficient path planning in parking scenarios presents a significant challenge due to the presence of cluttered environments filled with static and dynamic obstacles. To ad…
Frenet Corridor Planner: An Optimal Local Path Planning Framework for Autonomous Driving
Faizan M. Tariq, Zheng-Hang Yeh, Avinash Singh +2
Motivated by the requirements for effectiveness and efficiency, path-speed decomposition-based trajectory planning methods have widely been adopted for autonomous driving applicati…
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…
Delayed-Decision Motion Planning in the Presence of Multiple Predictions
David Isele, Alexandre Miranda Anon, Faizan M. Tariq +3
Reliable automated driving technology is challenged by various sources of uncertainties, in particular, behavioral uncertainties of traffic agents. It is common for traffic agents…
Predictive Planner for Autonomous Driving with Consistency Models
Anjian Li, Sangjae Bae, David Isele +2
Trajectory prediction and planning are essential for autonomous vehicles to navigate safely and efficiently in dynamic environments. Traditional approaches often treat them separat…
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…