Shahpour Alirezaee

Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration

Manveen Kaur, Rajmeet Singh, Saeed Mozaffri, Shahpour Alirezaee

Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measurement with thread or caliper is accurate but infeasible at commercial scale. This paper presents CucumberVision, a non-contact length estimation framework using an Intel …

Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration

Manveen Kaur, Rajmeet Singh, Saeed Mozaffri, Shahpour Alirezaee

Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measurement with thread or caliper is accurate but infeasible at commercial scale. This paper presents CucumberVision, a non-contact length estimation framework using an Intel …

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CLIP-BEV: A Late-Fusion Framework for Multimodal Scene Understanding Using Vision Language Models

Fatemeh Daraee, Saeed Mozaffari, Shahpour Alirezaee

Scene understanding is a fundamental task in autonomous driving, requiring effective integration of semantic and geometric information from heterogeneous sensors. Although vision–language models (VLMs) provide powerful semantic representations, their integration with LiDAR-based geometric perception remains challenging. This paper proposes a multimodal late-fusion …

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YOLO26-RipeLoc Lite: A lightweight architecture for tomato ripeness detection and picking point localization in greenhouse robotic harvesting

Rajmeet Singh, Manveen Kaur, Shahpour Alirezaee, Irfan Hussain

In greenhouse tomato production, automated harvesting requires accurate detection of ripe tomatoes, ripeness classification, and precise picking-point localization for robotic end-effectors. This paper proposes YOLO26-RipeLoc Lite, a lightweight deep learning architecture based on YOLO26 for simultaneous detection, ripeness classification, and center-point localization …

YOLO26-RipeLoc Lite: A lightweight architecture for tomato ripeness detection and picking point localization in greenhouse robotic harvesting

Rajmeet Singh, Manveen Kaur, Shahpour Alirezaee, Irfan Hussain

In greenhouse tomato production, automated harvesting requires accurate detection of ripe tomatoes, ripeness classification, and precise picking-point localization for robotic end-effectors. This paper proposes YOLO26-RipeLoc Lite, a lightweight deep learning architecture based on YOLO26 for simultaneous detection, ripeness classification, and center-point localization …

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Integrating Large Language Models with ROS 2 for Waypoint-Based Mobile Robot Navigation

Tariq Zamzam, Reza Alirezaee, Saeed Mozaffari, Shahpour Alirezaee

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Vision Language Action for TurtleBot Mobile Robot Path Planning

Noor Oush, Reza Alirezaee, Saeed Mozaffari, Shahpour Alirezaee

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Torque-Aware Path Planning for Robot Manipulators Using Artificial Potential Fields

Ehsan Maani Miandoab, Seyed Mani Mirshabani, Saeed Mozaffari, Shahpour Alirezaee

This study presents a novel approach for path planning of a manipulator’s end effector, integrating motor torque constraints into the path planning process. Unlike traditional Artificial Potential Field (APF) methods that focus solely on geometric and kinematic constraints, the proposed technique incorporates …

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Enhancing vehicle lane change prediction via transfer learning infused with social interaction dynamics

Alireza Mirzabagheri, Saeed Mozaffari, Shahpour Alirezaee

Advances in Cellular Vehicle-to-Everything (C-V2X) and Fifth Generation (5G) technologies have enabled the Internet of Vehicles (IoV), facilitating seamless information sharing for autonomous driving. However, accurate lane change prediction (LCP) remains a significant challenge due to the complexity of vehicle motion and …

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Visual-language transformer-based tomato leaf disease detection for portable greenhouse monitoring device

Manveen Kaur, Rajmeet Singh, Shahpour Alirezaee, Irfan Hussain

Tomato leaf diseases pose a significant threat to global food security, necessitating accurate and efficient detection methods. This paper introduces the Tomato Leaf Disease Visual Language Model (TLDVLM), a novel approach based on the BLIP-2 architecture enhanced with Low-Rank Adaptation (LoRA), for …

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Visual-Language Transformer-Based Tomato Leaf Disease Detection for Portable Greenhouse Monitoring Device

Manveen Kaur, Rajmeet Singh, Shahpour Alirezaee, Irfan Hussain

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Limit Cycle-Based Artificial Fields for Obstacle Avoidance in Robot Path Planning

Ali Mahdian, Ehsan Maani Miandoab, Saeed Mozaffari, Shahpour Alirezaee

This paper introduces a novel limit cycle-based approach for obstacle avoidance and compares its performance against the conventional Attractive-Repulsive method, a widely used artificial potential field (APF) technique. While traditional APF methods model obstacles as repulsive fields and the goal as an …

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