16 citations · 33 across the 12 of their papers we have counts for
12 papers
Iterative Grasp Pose Refinement: A Deep Reinforcement Learning Approach for 2D Vision
Amir Arsalan Nematollahi, Shayan Ahmadi, Mehdi Tale Masouleh +1
Developing robots capable of understanding and manipulating objects requires compact, interpretable, and generalizable representations. This work proposes a reinforcement learning-…
Push-Placement: A Hybrid Approach Integrating Prehensile and Non-Prehensile Manipulation for Object Rearrangement
Majid Sadeghinejad, Arman Barghi, Hamed Hosseini +2
Efficient tabletop rearrangement remains challenging due to collisions and the need for temporary buffering when target poses are obstructed. Prehensile pick-and-place provides pre…
Dynamic Buffers: Cost-Efficient Planning for Tabletop Rearrangement with Stacking
Arman Barghi, Hamed Hosseini, Seraj Ghasemi +2
Rearranging objects in cluttered tabletop environments remains a long-standing challenge in robotics. Classical planners often generate inefficient, high-cost plans by moving objec…
Grasp the Graph (GtG) 2.0: Ensemble of Graph Neural Networks for High-Precision Grasp Pose Detection in Clutter
Ali Rashidi Moghadam, Sayedmohammadreza Rastegari, Mehdi Tale Masouleh +1
Grasp pose detection in cluttered, real-world environments remains a significant challenge due to noisy and incomplete sensory data combined with complex object geometries. This pa…
Real-Time Imitation of Human Head Motions, Blinks and Emotions by Nao Robot: A Closed-Loop Approach
Keyhan Rayati, Amirhossein Feizi, Alireza Beigy +3
This paper introduces a novel approach for enabling real-time imitation of human head motion by a Nao robot, with a primary focus on elevating human-robot interactions. By using th…
AI-Driven Relocation Tracking in Dynamic Kitchen Environments
Arash Nasr Esfahani, Hamed Hosseini, Mehdi Tale Masouleh +2
As smart homes become more prevalent in daily life, the ability to understand dynamic environments is essential which is increasingly dependent on AI systems. This study focuses on…
Scene Understanding in Pick-and-Place Tasks: Analyzing Transformations Between Initial and Final Scenes
Seraj Ghasemi, Hamed Hosseini, MohammadHossein Koosheshi +2
With robots increasingly collaborating with humans in everyday tasks, it is important to take steps toward robotic systems capable of understanding the environment. This work focus…
Improving the Successful Robotic Grasp Detection Using Convolutional Neural Networks
Hamed Hosseini, Mehdi Tale Masouleh, Ahmad Kalhor
Robotic grasp should be carried out in a real-time manner by proper accuracy. Perception is the first and significant step in this procedure. This paper proposes an improved pipeli…
AGILE: Approach-based Grasp Inference Learned from Element Decomposition
MohammadHossein Koosheshi, Hamed Hosseini, Mehdi Tale Masouleh +2
Humans, this species expert in grasp detection, can grasp objects by taking into account hand-object positioning information. This work proposes a method to enable a robot manipula…
IsoCost-Based Dynamic Programming for Solving Infinite Horizon Optimal Control Problems
Saeed Rahimi, Amir Salimi Lafmejani, Ahmad Kalhor
An innovative numerical algorithm for solving infinite-horizon optimal control problems is introduced in this paper, using the IsoCost-HyperSurface (ICHS) concept. In the state spa…
Real-Time Facial Expression Recognition using Facial Landmarks and Neural Networks
Mohammad Amin Haghpanah, Ehsan Saeedizade, Mehdi Tale Masouleh +1
This paper presents a lightweight algorithm for feature extraction, classification of seven different emotions, and facial expression recognition in a real-time manner based on sta…
A Deep Learning Based Automated Hand Hygiene Training System
Mobina Shahbandeh, Fatemeh Ghaffarpour, Sina Vali +4
Hand hygiene is crucial for preventing viruses and infections. Due to the pervasive outbreak of COVID-19, wearing a mask and hand hygiene appear to be the most effective ways for t…