1 citations · 2 across the 28 of their papers we have counts for
10 papers · 1 filter
What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models
Amirhosein Chahe, Tyler Naes, Jovin D'sa +4
Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view. Current approaches often treat all occlusions with uniform con…
HOLO-MPPI: Multi-Scenario Motion Planning via Hierarchical Policy Optimization
Youngjae Min, Jovin D'sa, Faizan M. Tariq +3
Robots deployed in the real world must plan motions across diverse scenarios without per-scenario retuning. End-to-end reinforcement learning (RL) can generalize across scenarios b…
Exact, Efficient, and Safe Occlusion-Aware Planning Using AH-Polyhedrons
Long Kiu Chung, David Isele, Toktam Mohammadnejad +4
Safely handling occlusions is a fundamental challenge for autonomous mobile robots operating in dynamic environments. This issue is especially prominent in autonomous valet parking…
VLM-Based Advanced Rider Assistance System for Motorcycle Safety
Mohamed Elnoor, Francesca Baldini, Ananya Trivedi +6
Motorcycles face disproportionately high crash risks compared to cars due to limited protection and heightened sensitivity to surface hazards, yet Advanced Rider Assistance Systems…
N3P: Accelerated Automated Parking via a Learning-Based Naturalistic Three-Stage Scheme
Yifan Xue, Toktam Mohammadnejad, Faizan M Tariq +5
Autonomous parking requires efficient path planning that ensures kinematic feasibility and collision avoidance in constrained environments. Hybrid A* is widely used but computation…
Selecting Spots by Explicitly Predicting Intention from Motion History Improves Performance in Autonomous Parking
Long Kiu Chung, David Isele, Faizan M. Tariq +3
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 accep…
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…
ONRAP: Occupancy-driven Noise-Resilient Autonomous Path Planning
Faizan M. Tariq, Avinash Singh, Vipul Ramtekkar +4
Dynamic path planning must remain reliable in the presence of sensing noise, uncertain localization, and incomplete semantic perception. We propose a practical, implementation-frie…
Adaptive Time Step Flow Matching for Autonomous Driving Motion Planning
Ananya Trivedi, Anjian Li, Mohamed Elnoor +7
Autonomous driving requires reasoning about interactions with surrounding traffic. A prevailing approach is large-scale imitation learning on expert driving datasets, aimed at gene…
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…