AIConfPaper
← Search

Faizan M. Tariq

4 accepted papers

2026

Occupancy-Aware Trajectory Planning for Autonomous Valet Parking in Uncertain Dynamic Environments

Farhad Nawaz Savvas Sadiq Ali, Faizan M. Tariq, Sangjae Bae, David Isele, Avinash Singh, Nadia Figueroa +2
ICRA 2026poster

Autonomous Valet Parking (AVP) requires planning under partial observability, where parking spot availability evolves as dynamic agents enter and exit spots. Existing approaches either rely only on instantaneous spot availability or make static assumptions, thereby limiting foresight and adaptabilit…

Cited by 0Source ↗PDF ↗Scholar ↗
2026

Selecting Spots by Explicitly Predicting Intention from Motion History Improves Performance in Autonomous Parking

Long Kiu Chung, David Isele, Faizan M. Tariq, Sangjae Bae, Shreyas Kousik, Jovin D'sa
ICRA 2026poster

In many applications of social navigation, existing works have shown that predicting and reasoning about human intentions can help robotic agents make safer and more socially acceptable decisions. In this work, we study this problem for autonomous valet parking (AVP), where an autonomous vehicle ego…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Active Probing with Multimodal Predictions for Motion Planning

Darshan Gadginmath, Farhad Nawaz, Minjun Sung, Faizan M. Tariq, Sangjae Bae, David Isele +2
IROS 2025

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 combines trajectory planning with multimodal predictions and active probing to enhance decision-making under uncertainty.

Cited by 4Source ↗Scholar ↗
2025

Delayed-Decision Motion Planning in the Presence of Multiple Predictions

David Isele, Alexandre Miranda Añon, Faizan M. Tariq, Goro Yeh, Avinash T. Singh, Sangjae Bae
ICRA 2025

Reliable automated driving technology is challenged by various sources of uncertainties, in particular, behavioral uncertainties of traffic agents. It is common for traffic agents to have intentions that are unknown to others, leaving an automated driving car to reason over multiple possible behavio

Cited by 5Source ↗Scholar ↗