5 citations · 26 across the 40 of their papers we have counts for
42 papers
VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models
Ruiqi Xian, Yuehan Xian, Jing Liang +2
Semantic 3D occupancy provides a voxelized world state for autonomous driving and robot decision making, but object and rare-class errors can affect free-space interpretation, coll…
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…
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…
MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models
Xiyang Wu, Zongxia Li, Jihui Jin +7
Vision Language Models (VLMs) perform well on standard video tasks but struggle with physics-related reasoning involving motion dynamics and spatial interactions. We present a nove…
Bi-VLM: Pushing Ultra-Low Precision Post-Training Quantization Boundaries in Vision-Language Models
Xijun Wang, Junyun Huang, Rayyan Abdalla +3
We address the critical gap between the computational demands of vision-language models and the possible ultra-low-bit weight precision (bitwidth bits) we can use for highe…
NavMoE: Hybrid Model- and Learning-based Traversability Estimation for Local Navigation via Mixture of Experts
Botao He, Amir Hossein Shahidzadeh, Yu Chen +8
This paper explores traversability estimation for robot navigation. A key bottleneck in traversability estimation lies in efficiently achieving reliable and robust predictions whil…
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.…
MOSU: Autonomous Long-range Robot Navigation with Multi-modal Scene Understanding
Jing Liang, Kasun Weerakoon, Daeun Song +3
We present MOSU, a novel autonomous long-range navigation system that enhances global navigation for mobile robots through multimodal perception and on-road scene understanding. MO…
VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understanding
Zongxia Li, Xiyang Wu, Guangyao Shi +6
Vision-Language Models (VLMs) have achieved strong results in video understanding, yet a key question remains: do they truly comprehend visual content or only learn shallow correla…
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…
AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning
Yangzhe Kong, Daeun Song, Jing Liang +3
We present a novel method, AutoSpatial, an efficient approach with structured spatial grounding to enhance VLMs' spatial reasoning. By combining minimal manual supervision with lar…
Social-LLaVA: Enhancing Robot Navigation through Human-Language Reasoning in Social Spaces
Amirreza Payandeh, Daeun Song, Mohammad Nazeri +6
Most existing social robot navigation techniques either leverage hand-crafted rules or human demonstrations to connect robot perception to socially compliant actions. However, ther…
BehAV: Behavioral Rule Guided Autonomy Using VLMs for Robot Navigation in Outdoor Scenes
Kasun Weerakoon, Mohamed Elnoor, Gershom Seneviratne +5
We present BehAV, a novel approach for autonomous robot navigation in outdoor scenes guided by human instructions and leveraging Vision Language Models (VLMs). Our method interpret…
ET-Former: Efficient Triplane Deformable Attention for 3D Semantic Scene Completion From Monocular Camera
Jing Liang, He Yin, Xuewei Qi +4
We introduce ET-Former, a novel end-to-end algorithm for semantic scene completion using a single monocular camera. Our approach generates a semantic occupancy map from single RGB…
Robot Navigation Using Physically Grounded Vision-Language Models in Outdoor Environments
Mohamed Elnoor, Kasun Weerakoon, Gershom Seneviratne +5
We present a novel autonomous robot navigation algorithm for outdoor environments that is capable of handling diverse terrain traversability conditions. Our approach, VLM-GroNav, u…
FALCON: Future-Aware Learning with Contextual Object-Centric Pretraining for UAV Action Recognition
Ruiqi Xian, Xiyang Wu, Tianrui Guan +3
We introduce FALCON, a unified self-supervised video pretraining approach for UAV action recognition from raw RGB aerial footage, requiring no additional preprocessing at inference…
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…
GND: Global Navigation Dataset with Multi-Modal Perception and Multi-Category Traversability in Outdoor Campus Environments
Jing Liang, Dibyendu Das, Daeun Song +6
Navigating large-scale outdoor environments requires complex reasoning in terms of geometric structures, environmental semantics, and terrain characteristics, which are typically c…
VLPG-Nav: Object Navigation Using Visual Language Pose Graph and Object Localization Probability Maps
Senthil Hariharan Arul, Dhruva Kumar, Vivek Sugirtharaj +6
We present VLPG-Nav, a visual language navigation method for guiding robots to specified objects within household scenes. Unlike existing methods primarily focused on navigating th…
TOPGN: Real-time Transparent Obstacle Detection using Lidar Point Cloud Intensity for Autonomous Robot Navigation
Kasun Weerakoon, Adarsh Jagan Sathyamoorthy, Mohamed Elnoor +2
We present TOPGN, a novel method for real-time transparent obstacle detection for robot navigation in unknown environments. We use a multi-layer 2D grid map representation obtained…
VL-TGS: Trajectory Generation and Selection using Vision Language Models in Mapless Outdoor Environments
Daeun Song, Jing Liang, Xuesu Xiao +1
We present a multi-modal trajectory generation and selection algorithm for real-world mapless outdoor navigation in human-centered environments. Such environments contain rich feat…
CSCPR: Cross-Source-Context Indoor RGB-D Place Recognition
Jing Liang, Zhuo Deng, Zheming Zhou +5
We extend our previous work, PoCo, and present a new algorithm, Cross-Source-Context Place Recognition (CSCPR), for RGB-D indoor place recognition that integrates global retrieval…
AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models
Xiyang Wu, Tianrui Guan, Dianqi Li +9
Large vision-language models (LVLMs) are prone to hallucinations, where certain contextual cues in an image can trigger the language module to produce overconfident and incorrect r…
GAMEOPT+: Improving Fuel Efficiency in Unregulated Heterogeneous Traffic Intersections via Optimal Multi-agent Cooperative Control
Nilesh Suriyarachchi, Rohan Chandra, Arya Anantula +2
Better fuel efficiency leads to better financial security as well as a cleaner environment. We propose a novel approach for improving fuel efficiency in unstructured and unregulate…