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Practical matters How to find us S.H. (Hamidreza) Mohades Kasaei, PhD

Research interests

My research interest lies at the intersection of machine learning, robotics, and machine vision, particularly, at the area of open-ended learning, 3D object perception, grasp affordance detection, and object manipulation. I am interested in developing algorithms for an adaptive perception system based on interactive environment exploration and open-ended learning, which enables robots to learn from past experiences and interact with human users. I have been investigating on active perception, where robots use their mobility and manipulation capabilities not only to gain perceptual information to model the world but also to predict the next-best-view for improving object detection and manipulation performances. I have evaluated my works on different robotic platforms, including PR2, robotic arms (UR5e, Kinova, Franka), and humanoid robots. For more details, please check my webpage  www.ai.rug.nl/hkasaei

Publications

Explain What You See: Open-Ended Segmentation and Recognition of Occluded 3D Objects

MVGrasp: Real-time multi-view 3D object grasping in highly cluttered environments

A Hybrid Compositional Reasoning Approach for Interactive Robot Manipulation

A Strong Transfer Baseline for RGB-D Fusion in Vision Transformers

Lifelong 3D object recognition and grasp synthesis using dual memory recurrent self-organization networks

Lifelong Ensemble Learning based on Multiple Representations for Few-Shot Object Recognition

Local-HDP: Interactive open-ended 3D object category recognition in real-time robotic scenarios

Obstacle Avoidance for Robotic Manipulator in Joint Space via Improved Proximal Policy Optimization

Throwing Objects into A Moving Basket While Avoiding Obstacles

3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks

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