Saeid Nahavandi
YOU?
Author Swipe
View article: Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning
Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning Open
Enabling multiple autonomous machines to perform reliably requires the development of efficient cooperative control algorithms. This paper presents a survey of algorithms that have been developed for controlling and coordinating autonomous…
View article: Advancing Cognitive Load Detection in Simulated Driving Scenarios Through Deep Learning and fNIRS Data
Advancing Cognitive Load Detection in Simulated Driving Scenarios Through Deep Learning and fNIRS Data Open
The shift from manual to conditionally automated driving, supported by Advanced Driving Assistance Systems (ADASs), introduces challenges, particularly increased crash risks due to human factors like cognitive overload. Driving simulators …
View article: Enhancing Oral Surgery Simulation: A Systematic Review of 3D‐Printed Patient‐Specific Models Compared to Traditional Animal Jaw Models for Presurgical Training
Enhancing Oral Surgery Simulation: A Systematic Review of 3D‐Printed Patient‐Specific Models Compared to Traditional Animal Jaw Models for Presurgical Training Open
Objectives 3D‐printed simulation models are emerging as novel tools in various medical education fields. This study aims to investigate the evidence on the efficacy of 3D‐printed jaw models compared to traditional animal models for oral su…
View article: The Emergence of Deep Reinforcement Learning for Path Planning
The Emergence of Deep Reinforcement Learning for Path Planning Open
The increasing demand for autonomous systems in complex and dynamic environments has driven significant research into intelligent path planning methodologies. For decades, graph-based search algorithms, linear programming techniques, and e…
View article: Real Time Classification of Cognitive Load Using fNIRS and EEGNet in a Driving Simulation Task
Real Time Classification of Cognitive Load Using fNIRS and EEGNet in a Driving Simulation Task Open
Understanding and monitoring cognitive workload is essential for ensuring safety and performance in cognitively demanding environments such as driving. In this study, we investigate the effectiveness of Functional Near-Infrared Spectroscop…
View article: Advancing Cognitive Load Detection in Simulated Driving Scenarios Through Deep Learning and fNIRS Data
Advancing Cognitive Load Detection in Simulated Driving Scenarios Through Deep Learning and fNIRS Data Open
The shift from manual to conditionally automated driving, supported by Advanced Driving Assistance Systems (ADAS), introduces challenges, particularly increased crash risks due to human factors like cognitive overload. Driving simulators p…
View article: Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing
Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing Open
Although neural networks (especially deep neural networks) have achieved better-than-human performance in many fields, their real-world deployment is still questionable due to the lack of awareness about the limitations in their knowledge.…
View article: A Comprehensive Review on Autonomous Navigation
A Comprehensive Review on Autonomous Navigation Open
The field of autonomous mobile robots has undergone dramatic advancements over the past decades. Despite achieving important milestones, several challenges are yet to be addressed. Aggregating the achievements of the robotic community as s…
View article: A nonlinear real time capable motion cueing algorithm based on deep reinforcement learning
A nonlinear real time capable motion cueing algorithm based on deep reinforcement learning Open
In motion simulation, motion cueing algorithms are used for the trajectory planning of the motion simulator platform, where workspace limitations prevent direct reproduction of reference trajectories. Strategies such as motion washout, whi…
View article: Evaluating the impact of music tempo on drivers and their performance using an artificial intelligence model: a multi-source data approach
Evaluating the impact of music tempo on drivers and their performance using an artificial intelligence model: a multi-source data approach Open
Traffic accidents are a major global health and economic concern. As such, research into understanding driving behaviors becomes essential to minimize the associated risks. Among various factors that can influence driving behaviors, listen…
View article: Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis
Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis Open
Functional near-infrared spectroscopy (fNIRS) is employed as a non-invasive method to monitor functional brain activation by capturing changes in the concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR). Various …
View article: Vision‐Language Hazard Reasoning for Driver Distraction and Workload Estimation
Vision‐Language Hazard Reasoning for Driver Distraction and Workload Estimation Open
Driver distraction and cognitive overload are major contributors to road accidents, especially in semi‐automated driving where humans must remain situationally aware. We propose an agentic reasoning approach for jointly detecting external …
View article: Object-Level Cross-View Geolocalization With Location Enhancement and Multihead Cross Attention
Object-Level Cross-View Geolocalization With Location Enhancement and Multihead Cross Attention Open
Cross-view geolocalization determines the location of a query image, captured by a drone or ground-based camera, by matching it to a georeferenced satellite image. While traditional approaches focus on image-level localization, many applic…
View article: HERCULES: Haptically-Enabled Remotely Controlled Ultrasound Examination System
HERCULES: Haptically-Enabled Remotely Controlled Ultrasound Examination System Open
The main purpose of the study is to investigate and demonstrate the feasibility and practicality of using a haptically-enabled remotely controlled ultrasound examination system (HERCULES) to perform point-of-care ultrasound. Robotic ultras…
View article: Barrier Lyapunov Function-based Backstepping Controller Design for Path Tracking of Autonomous Vehicles
Barrier Lyapunov Function-based Backstepping Controller Design for Path Tracking of Autonomous Vehicles Open
This research proposes a novel BLF-based backstepping controller for path tracking of Autonomous Vehicles (AVs) with unknown dynamics and unmeasurable states. The proposed framework includes: (1) forming geometric-dynamic model of the vehi…
View article: Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model
Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model Open
One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving. Although physiological signals have been extensively used in driving-related research to assess …
View article: Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis
Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis Open
Functional near-infrared spectroscopy (fNIRS) is employed as a non-invasive method to monitor functional brain activation by capturing changes in the concentrations of oxygenated haemoglobin (HbO) and deoxygenated haemo-globin (HbR). Vario…
View article: Application of artificial intelligence in cognitive load analysis using functional near-infrared spectroscopy: A systematic review
Application of artificial intelligence in cognitive load analysis using functional near-infrared spectroscopy: A systematic review Open
Cognitive load theory suggests that overloading of working memory may negatively affect the performance of human in cognitively demanding tasks. Evaluation of cognitive load is a difficult task; it is often assessed through feedback and ev…
View article: Investigating the influence of neck muscle vibration on illusory self-motion in virtual reality
Investigating the influence of neck muscle vibration on illusory self-motion in virtual reality Open
The illusory experience of self-motion known as vection, is a multisensory phenomenon relevant to self-motion processes. While some studies have shown that neck muscle vibrations can improve self-motion parameter estimation, the influence …
View article: Machine learning meets advanced robotic manipulation
Machine learning meets advanced robotic manipulation Open
Automated industries lead to high quality production, lower manufacturing cost and better utilization of human resources. Robotic manipulator arms have major role in the automation process. However, for complex manipulation tasks, hard cod…