23 citations · 51 across the 35 of their papers we have counts for
39 papers
CoPlanVLM: Coordinated Path Planning for a Robot Team using Vision Language Models
David R. Martin, Jared Paquet, Mohammad Abdullah Al Faruque +4
We present CoPlanVLM, which uses a Vision Language Model (VLM) to translate a single natural-language instruction and image into coordinated paths for a team of two robots. While V…
CORNAV: Construction-Aware Reasoning for Robot Navigation on Active Worksites
Parastoo Ali Pour, Deepak Prakash Kumar, Tommy Zhou +2
The construction industry faces persistent labor shortages, low productivity that costs the global economy over $1.6 trillion annually, and one of the highest injury rates among ma…
Toward Humanoid Robots in Construction: A Teleoperation Feasibility Study
Parastoo Ali Pour, David R. Martin, Chang Min Hur +6
We present a teleoperation system that enables a single operator to perform construction tasks on a Unitree G1 humanoid, combining extended reality (XR) based upper body control wi…
EdgeDAE: Acceleration of Diffusion Action Experts for Real-Time Physical AI with Tiny VLAs on Edge FPGA-GPU Systems
Zhiheng Chen, Ye Qiao, Mohammad Abdullah Al Faruque +1
Physical AI models such as Vision-Language-Action (VLA) architectures enable generalist robotic policies through large-scale transformer backbones and diffusion-based action decode…
A Direct Rigid Transmission 2-DoF Wrist Extension for Tendon-Driven Hand
Yujie Pang, Sadman Sakib, Mohammad Abdullah Al Faruque
Dexterous manipulation in confined spaces requires local control of hand orientation. Without a wrist, a dexterous hand must obtain this local orientation through coordinated motio…
A Taxonomy of Construction Task Activities for Robot Workers
Sadman Sakib, Zhangyi None Peng, Zhangyi Peng +3
Recent vision-language-action models offer a path toward robots with broader capabilities than conventional task-specific systems. Deploying such systems in construction, however,…
VikPath: A Vision Kansformer Framework for Effective Obstacle Avoidance in Self-Supervised Pathfinding
Junyao Wang, Yulin Xu, Mohammad Abdullah Al Faruque
Pathfinding is a fundamental problem in artificial intelligence and autonomous systems. Traditional heuristic-based algorithms, such as A*, rely on predefined heuristic functions t…
CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving
Junyao Wang, Yulin Xu, Yu Li +2
Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception. However, robust cross-modal feature fu…
Do Agents Dream of False Memories? Black-box Visual Attacks on Long-term Memory in Multimodal AI Agents
Halima Bouzidi, Mboutidem Ekemini Mkpong, Mohammad Abdullah Al Faruque
Multimodal AI agents increasingly rely on persistent long-term memory to ground generation in past visual and textual episodes. We show that unconditional trust in visual data crea…
Edge Physical AI Deployment of Vision Transformers on Heterogeneous Edge GPU Targeting Autonomous Vehicles
Ashiyana Abdul Majeed, Mahmoud Meribout, Neethu Joseph +2
Physical AI systems, such as autonomous vehicles and intelligent machines, require transformer-based perception models that satisfy stringent edge latency and energy constraints. H…
HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems
Luke Chen, Cheng-Ju Wu, David R. Martin +3
Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-perception systems face an inherent…
Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations
Halima Bouzidi, Mboutidem Ekemini Mkpong, Haoyu Liu +1
Generative models have recently seen rapid adoption in End-to-End (E2E) autonomous driving (AD), with diffusion-based denoising and vocabulary-based retrieval becoming the dominant…
Radiance Field Delta Video Compression in Edge-Enabled Vehicular Metaverse
Matúš Dopiriak, Eugen Šlapak, Juraj Gazda +3
Connected and autonomous vehicles (CAVs) offload computationally intensive tasks to multi-access edge computing (MEC) servers via vehicle-to-infrastructure (V2I) communication, ena…
SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators
Mohanad Odema, Luke Chen, Hyoukjun Kwon +1
Emerging multi-model workloads with heavy models like recent large language models significantly increased the compute and memory demands on hardware. To address such increasing de…
SMORE: Similarity-based Hyperdimensional Domain Adaptation for Multi-Sensor Time Series Classification
Junyao Wang, Mohammad Abdullah Al Faruque
Many real-world applications of the Internet of Things (IoT) employ machine learning (ML) algorithms to analyze time series information collected by interconnected sensors. However…
Distributed Radiance Fields for Edge Video Compression and Metaverse Integration in Autonomous Driving
Eugen Šlapak, Matúš Dopiriak, Mohammad Abdullah Al Faruque +2
The metaverse is a virtual space that combines physical and digital elements, creating immersive and connected digital worlds. For autonomous mobility, it enables new possibilities…
Rampo: A CEGAR-based Integration of Binary Code Analysis and System Falsification for Cyber-Kinetic Vulnerability Detection
Kohei Tsujio, Mohammad Abdullah Al Faruque, Yasser Shoukry
This paper presents a novel tool, named Rampo, that can perform binary code analysis to identify cyber kinetic vulnerabilities in CPS. The tool takes as input a Signal Temporal Log…
Inter-Layer Scheduling Space Exploration for Multi-model Inference on Heterogeneous Chiplets
Mohanad Odema, Hyoukjun Kwon, Mohammad Abdullah Al Faruque
To address increasing compute demand from recent multi-model workloads with heavy models like large language models, we propose to deploy heterogeneous chiplet-based multi-chip mod…
Robust and Scalable Hyperdimensional Computing With Brain-Like Neural Adaptations
Junyao Wang, Mohammad Abdullah Al Faruque
The Internet of Things (IoT) has facilitated many applications utilizing edge-based machine learning (ML) methods to analyze locally collected data. Unfortunately, popular ML algor…
DOMINO: Domain-invariant Hyperdimensional Classification for Multi-Sensor Time Series Data
Junyao Wang, Luke Chen, Mohammad Abdullah Al Faruque
With the rapid evolution of the Internet of Things, many real-world applications utilize heterogeneously connected sensors to capture time-series information. Edge-based machine le…
MaGNAS: A Mapping-Aware Graph Neural Architecture Search Framework for Heterogeneous MPSoC Deployment
Mohanad Odema, Halima Bouzidi, Hamza Ouarnoughi +2
Graph Neural Networks (GNNs) are becoming increasingly popular for vision-based applications due to their intrinsic capacity in modeling structural and contextual relations between…
CARMA: Context-Aware Runtime Reconfiguration for Energy-Efficient Sensor Fusion
Yifan Zhang, Arnav Vaibhav Malawade, Xiaofang Zhang +4
Autonomous systems (AS) are systems that can adapt and change their behavior in response to unanticipated events and include systems such as aerial drones, autonomous vehicles, and…
Stress Detection using Context-Aware Sensor Fusion from Wearable Devices
Nafiul Rashid, Trier Mortlock, Mohammad Abdullah Al Faruque
Wearable medical technology has become increasingly popular in recent years. One function of wearable health devices is stress detection, which relies on sensor inputs to determine…
ERUDITE: Human-in-the-Loop IoT for an Adaptive Personalized Learning System
Mojtaba Taherisadr, Mohammad Abdullah Al Faruque, Salma Elmalaki
Thanks to the rapid growth in wearable technologies and recent advancement in machine learning and signal processing, monitoring complex human contexts becomes feasible, paving the…