collaborators

6 papers

cs.RO2026

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…

cs.RO2026

ViLAM: Distilling Vision-Language Reasoning into Attention Maps for Social Robot Navigation

Mohamed Elnoor, Kasun Weerakoon, Gershom Seneviratne +3

We introduce ViLAM, a novel method for distilling vision-language reasoning from large Vision-Language Models (VLMs) into spatial attention maps for socially compliant robot naviga…

cs.RO2026

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…

cs.RO2025

DR. Nav: Semantic-Geometric Representations for Proactive Dead-End Recovery and Navigation

Vignesh Rajagopal, Kasun Weerakoon Kulathun Mudiyanselage, Gershom Devake Seneviratne +5

We present DR. Nav (Dead-End Recovery-aware Navigation), a novel approach to autonomous navigation in scenarios where dead-end detection and recovery are critical, particularly in…

cs.RO2025

HALO: Human Preference Aligned Offline Reward Learning for Robot Navigation

Gershom Seneviratne, Jianyu An, Sahire Ellahy +5

In this paper, we introduce HALO, a novel Offline Reward Learning algorithm that quantifies human intuition in navigation into a vision-based reward function for robot navigation.…

cs.RO2025

CROSS-GAiT: Cross-Attention-Based Multimodal Representation Fusion for Parametric Gait Adaptation in Complex Terrains

Gershom Seneviratne, Kasun Weerakoon, Mohamed Elnoor +5

We present CROSS-GAiT, a novel algorithm for quadruped robots that uses Cross Attention to fuse terrain representations derived from visual and time-series inputs; including linear…