Perception and Manipulation

Dual-arm Manipulation

Neural Motion/Task Planning

Latest News

June 2025: I will co-organize a full day workshop on Building Physically Plausible World Models at ICML 2025.
June 2025: I will co-organize a full day workshop on R3: Reasoning for Robust Robot Manipulation in the Open World at RSS 2025.
March. 2025: Our paper titled Learning Dual-Arm Push and Grasp Synergy in Dense Clutte got accepted to IEEE Robotics and Aumation Letters (RA-L)! [webpage]
April 2025: I will co-organize 7th Robot Learning Workshop on Towards Robots with Human-Level Abilitieson at ICLR 2025.
Jan. 2025: Two papers accepted at ICRA'25, one of the premier conferences in robotics. A big thank you to my students!
1- Learning Dual-Arm Coordination for Grasping Large Objects [webpage] [video]
2- Enhanced View Planning for Robotic Harvesting: Tackling Occlusions with Imitation Learning [video]
Nov. 2024: We have two multidisciplinary PhD positions focusing on cutting-edge research areas of Robotic Task Planning, Brain-Computer Interface, and Adaptive Visualization.
Oct. 2024: Two papers accepted at CoRL'24, one of the premier conferences in robot learning. A big thank you to my students and collaborators!
1- Towards Open-World Grasping with Large Vision-Language Models [webpage]
2- SoftManiSim: A Fast Simulation Framework for Multi-Segment Continuum Manipulators Tailored for Robot Learning [GitHub]
Jun. 2024: Our paper titled Single-Shot 6DoF Pose and 3D Size Estimation for Robotic Strawberry Harvesting got accepted to 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)!!
April. 2024: Our paper titled Simultaneous Multi-View Object Recognition and Grasping in Open-Ended Domains got accepted to Journal of Intelligent & Robotic Systems! - [open-access]!
Jan. 2024: Four papers accepted at ICRA'24, one of the premier conferences in robotics. A big thank you to my students and collaborators!
1- Lifelong Robot Library Learning: Bootstrapping Composable and Generalizable Skills for Embodied Control with Language Models
2- Harnessing the Synergy between Pushing, Grasping, and Throwing to Enhance Object Manipulation in Cluttered Scenarios
3- Self-supervised Learning for Joint Pushing and Grasping Policies in Highly Cluttered Environments
4- TiV-ODE: A Neural ODE-based Approach for Controllable Video Generation From Text-Image Pairs
Dec. 2023: Our paper titled Lifelong ensemble learning based on multiple representations for few-shot object recognition got accepted to Robotics and Autonomous Systems Journal! - [open-access]!
Sep. 2023: Our paper titled Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter got accepted to CORL! - [open-access]!
Sep. 2023: Our paper titled MORE: simultaneous multi-view 3D object recognition and pose estimation got accepted to Intelligent Service Robotics Journal! - [open-access]!
June. 2023: Three papers accepted at IROS'23, one of the premier conferences in robotics. A big thank you to my students and collaborators!
1- Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition [video]
2- Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models [video]
3- L3MVN: Leveraging Large Language Models for Visual Target Navigation [video]
June. 2023: Hamidreza Kasaei received Google Research Scholar Award in the field of Machine Learning for his work on Continual Robot Learning in Human-centered Environments! Congrats Hamidreza!
June. 2023: Hamidreza Kasaei has been selected as Outstanding Associate Editor for the IEEE Robotics and Automation Letters. Congrats Hamidreza!
April. 2023: Our paper titled MORE: Simultaneous Multi-View 3D Object Recognition and Pose Estimation got accepted to Intelligent Service Robotics! - [open-access]!
March. 2023: We will organize a full-day workshop on the topic of "Interdisciplinary Exploration of Generalizable Manipulation Policy Learning: Paradigms and Debates" at RSS 2023.
Feb. 2023: Zhenxing Zhang successfully defended his Ph.D. thesis Generative Adversarial Networks for Diverse and Explainable Text-to-Image Generation. Congratulation Zhenxing!
Jan. 2023: Hamed Ayoobi successfully defended his Ph.D. thesis Explain What You See: Argumentation-Based Learning and Robotic Vision. Congratulation Hamed!
Jan. 2023: Hamidreza Kasaei is serving as associate editor for the IROS 2023!
Jan. 2023: Four of our papers have been accepted at ICRA'23, the premier conference in robotics. A big thank you to my students and collaborators!
1- Throwing Objects into A Moving Basket While Avoiding Obstacles. [video]
2- Explain What You See: Open-Ended Segmentation and Recognition of Occluded 3D Objects. [video]
3- Instance-wise Grasp Synthesis for Robotic Grasping. [video]
4- Frontier Semantic Exploration for Visual Target Navigation [video]
Nov. 2022: Hamidreza Kasaei gave an invited talk at the AI & Robotics in Healthcare | Data Science Center in Health (DASH) on Towards Lifelong Assistive Robotics: How to make life easier for people with disabilities? [video]
Nov. 2022: Hamidreza Kasaei gave an invited talk at the University of Aveiro, Portugal | Seminar in Robotics and Intelligent Systems on Robotics for Society: How robots can help us with a wide variety of tasks in different domains incrementally?
Oct. 2022: Our paper titled MVGrasp: Real-Time Multi-View 3D Object Grasping in Highly Cluttered Environments got accepted to Robotics and Autonomous Systems (RAS)! - [open-access]!
Sep. 2022: Hamidreza Kasaei is serving as associate editor for the IEEE Robotics and Automation Letters (RA-L)! .
March. 2022: Our paper titled Sim-to-Real Transfer of Visual Grounding for Human-Aided Ambiguity Resolution got accepted to Conference on Lifelong Learning Agents (CoLLAs 2022)! Congrats Georgios!
Sep. 2022: Hamidreza Kasaei is serving as associate editor for the IEEE ICRA 2023! .
June 2022: We will organize a full-day workshop on 5th Robot Learning Workshop: Trustworthy Robotics at NeruIPS2022.
March. 2022: Our paper titled Lifelong 3D Object Recognition and Grasp Synthesis using Dual Memory Recurrent Self-Organization Networks got accepted to Neural Networks Journal! Congrats Krishna!
Jan. 2022: Hamidreza Kasaei is serving as associate editor for the IEEE/RSJ IROS 2022! .
Jan. 2022: Our paper titled Local-HDP: Interactive open-ended 3D object category recognition in real-time robotic scenarios got accepted to Robotics and Autonomous Systems (RAS)! Congrats Hamed!
Sep. 2021: Hamidreza Kasaei is serving as associate editor for the IEEE/RSJ ICRA 2022! .
July 2021: We will organize a full-day workshop on 4th Robot Learning Workshop: Self-Supervised and Lifelong Learning at NeruIPS2021.
July. 2021: Our paper titled The State of Lifelong Learning in Service Robots: Current Bottlenecks in Object Perception and Manipulation got accepted to Journal of Intelligent & Robotic Systems

Research Directions

In our group, we focus on Lifelong Interactive Robot Learning to make robots capable of learning in an open-ended fashion by interacting with non-expert human users. In particular, we have been developing this goal over the following six specific research directions. Details of our publications, including paper, demonstration, and code, can be found here!

Robot Perception and Perceptual Learning

We are interested in attaining a 3D understanding of the world around us. In particular, the perception system provides important information that the robot has to use for interacting with users and environments.

Object Grasping and Object Manipulation

A service robot must be able to interact with the environment as well as human users. We are interested in fundamental research in object-agnostic grasping, affordance detection, task-informed grasping, and object manipulation.

Lifelong Interactive Robot Learning

No matter how extensive the training data used for batch learning, a robot will always face new objects. Therefore, the robot should be able to continually learn about new tasks from few training examples on-site by interacting with non-expert users.

Dynamic Robot Motion Planning

We are interested in attaining fully reactive manipulation functionalities in a closed-loop manner. Reactive systems have to continuously check if they are at risk of colliding while planners should check every configuration that the robot may attempt to use.

Exploiting Multimodality

A service robot may sense the world through different modalities that may provide visual, haptic or auditory cues about the environment. In this vein, we are interested in exploiting multimodality for learning better representations to improve robot's performance.

Dual-Arm Manipulation

A dual-arm robot has very good manipulability and maneuverability which is necessary to accomplish a set of everyday tasks (dishwashing, hammering). We are interested in efficient imitation learning, collabrative manipulation, and large object manipulation.

People

Hamidreza Kasaei
Group Leader

Sha Luo
PhD Student

Georgios Tziafas
PhD Student

Songsong Xiong
PhD Student

Yongliang Wang
PhD Student

Hamed Ayoobi
PhD Student

Alen (Lun) Li
PhD Student

Bangguo Yu
PhD Student

David Boerema
PhD Student

Madhur Madhur
MSc Student

Daan Krol
MSc Student

Jeroen van Brandenburg
MSc Student

Koen Buiten
MSc Student

Kamal Mokhtar
MSc Student

Ivar Mak
MSc Student

Nachiket Desai
MSc Student

Andrei Miculita
MSc Student

Mario Cavero Vidal
MSc Student

Tomas van der Velde
MSc Student

Jos van Goor
MSc Student

Arjan Jawahier
MSc Student

Thijs Eker
MSc Student

Georgios Tziafas
MSc Student

Krishna Santhakumar
MSc Student

Hari Vidharth
MSc Student

Tommaso Parisotto
MSc Student

Sudhakaran Jain
MSc Student

Subilal Purayil
MSc Student

Yikun Li
MSc Student

Mario Rios-Munoz
MSc Student

Jeroen Oude Vrielink
MSc Student

Bart van Marum
MSc Student

Subhaditya Mukherjee
MSc Student

Ruben Spolmink
MSc Student

Vlad Iftime
MSc Student

Andreea Toca
MSc Student

Anne-Jan Mein
MSc Student

Juan Gonzalez
MSc Student

Jiayun Zhang
MSc Student

Remco Leijenaar
MSc Student

Jakob de Boer
MSc Student

Junhyung Jo
BSc Student

Jeroen Oude Vrielink
BSc Student

Anne-Jan Mein
BSc Student

Jim Wu
BSc Student

Vlad Iftime
BSc Student

Andreea Toca
BSc Student

Nils Keunecke
BSc Student

Roberto Navarro
BSc Student

Nikolai Herrmann
BSc Student

Iustin Lungu
BSc Student

Ids Andriesse
BSc Student

Students Projects

PhD Projects

  • Georgios Tziafas (Oct.2021 ~ )
  • Lifelong Learning for Dual-arm Manipulation Tasks in Human-centric Environments
  • Supervisor: Hamidreza Kasaei
  • 2nd Supervisor: Lambert Schomaker
  • Yongliang Wang (July.2022 ~ )
  • Self-Supervised Target-Driven Object Manipulation in Constrained Cluttered Environments
  • Supervisor: Hamidreza Kasaei
  • 2nd Supervisor: Lambert Schomaker
  • Alen (Lun) Li (Oct.2022 ~ )
  • Expanding the Manipulation Capabilities of Agricultural Bimanual Robots through Learning and Adaptation
  • Supervisor: Hamidreza Kasaei
  • 2nd Supervisor: Lambert Schomaker
  • Bangguo Yu (Oct.2021 ~ )
  • Socially aware Robot Navigation in Uncertain Scenes
  • Supervisor: Ming Cao
  • 2nd Supervisor: Hamidreza Kasaei

Sample Master Projects

Below are a few examples of Master projects conducted in our group. A complete list of BSc/MSc theses that have been completed in the IRL-Lab can be found here!
  • Madhur Madhur (July.2022 ~)
  • Dual-Arm Manipulation and Coordination for Object Placement
  • Daan Krol (May.2022 ~) [Intern at Intel]
  • Dataset Reduction Methods for Data and Energy Efficient Incremental Learning
Thesis
  • Koen Buiten (Oct.2021 ~ July 2022)
  • Multi-View 3D Object Recognition: Selecting the Best Sequences of Views
  • Ivar Mak (Oct.2021 ~ July 2022)
  • Target Driven Object Grasping in Highly Cluttered Scenarios through Domain Randomization and Active Segmentation
Code Thesis
  • Kamal Mokhtar (Oct.2021 ~ July 2022) [Intern at HiT]
  • Self-Supervised Learning for Joint Pushing and Grasping Policies in Highly Cluttered Environments
Paper Demo Code Thesis
  • Jos van Goor (Feb.2021 ~ )
  • Leveraging Deep Object Recognition Models for Per-Point 6-DOF Grasp Synthesis
  • Krishna Santhakumar (Feb.2021 ~ Sep.2021 )
  • Lifelong Object Grasp Synthesis using Dual Memory Recurrent Self-Organization Networks
Paper Demo Code Thesis
  • Arjan Jawahier (March.2021 ~ )
  • Descriptive Viewpoint Prediction: Simultaneous Object Recognition and Grasping in Service Robots
  • Hari Vidharth (Feb.2021 ~ )
  • Accelerating Multi-Goal Reinforcement Learning by Learning from Demonstrations for Robotic Manipulation Tasks
Thesis
  • Georgios Tziafas (Feb.2021 ~ Sep.2021 )
  • Sim2Real Transfer of Visiolinguistic Representations for Human-Robot Interaction
Paper Demo Thesis
  • Thijs Eker (Nov.2020 ~ Sep.2021) [Intern at TNO]
  • Classifying objects from unseen viewpoints using novel view synthesis data augmentation
Thesis
  • Tommaso Parisotto (July.2020 ~ March 2021)
  • MORE: Simultaneous Multi-View 3D Object Recognition and Grasp Pose Estimation
Paper Code Thesis
  • Sudhakaran Jain (March.2020 ~ Dec.2020)
  • Open-Ended 3D Object Recognition using Dynamically Evolving Neural Networks
Paper Demo Code Thesis
  • Subilal Vattimunda Purayil (April.2020 ~ Dec.2020)
  • Learning Deep Spatio-Temporal Features for Human Activity Classification
Thesis
  • Diego Cabo Golvano (Feb.2020 ~ Dec.2020)
  • Exploring Novel Hierarchical Reinforcement Learning Approaches to Lifelong Learning
Thesis
  • Yikun Li (Jan.2019 ~ Aug.2019)
  • Learning to Detect Grasp Affordances of 3D Objects using Deep Convolutional Neural Networks
 Paper Demo Dataset Thesis
  • Mario Rios-Munoz (Jan.2019 ~ Mar. 2020)
  • Learning to Grasp: A Deep Learning Approach to Generalized Robust Grasp Affordance
Paper Thesis Code

Sample Undergraduate Projects

Below are a few examples of Bachelor projects conducted in our group. A complete list of BSc/MSc theses that have been completed in the IRL-Lab can be found here!
  • Jeroen Oude Vrielink (Feb.2021 ~ )
  • Learning grasp affordances of 3D objects using Deep Convolutional Neural Networks
Proposal Thesis Page Demo Code
  • Anne-Jan Mein (Feb.2021 ~ )
  • Investigating the influences of different colour spaces in open-ended 3D recognition
Proposal Thesis Page
  • Junhyung Jo (Feb.2021 ~ )
  • Fine-grained 3D object recognition: an approach and experiments
Proposal Thesis Page
  • Jim Wu (Sep.2020 ~ Jan.2021 )
  • Lifelong 3D Object Recognition: a comparison of deep features and handcrafted descriptors
Thesis Page
  • Andreea Toca (Feb.2020 ~ July 2020)
  • Investigating the Importance of Color Spaces and Similarity Measures in Open-Ended 3D Object Recognition
Proposal Thesis Page
  • Vlad Iftime (Feb.2020 ~ July 2020)
  • Autoencoder-based Representation Learning for 3D Object Recognition in Open-Ended Domains
Proposal Thesis Page
  • Roberto Navarro (Feb.2020 ~ July 2020)
  • Learning to Grasp 3D objects using Deep Convolutional Neural Network
Proposal Thesis Page
  • Nils Keunecke (Feb.2020 ~ July 2020)
  • 3D Object Recognition using OrthographicNet and Color Constancy
Proposal Thesis Page paper
  • Sandra Bedrossian (Jan2019 ~ July2019)
  • Vehicle License Plate Recognition using Pixel Information
Proposal Thesis Page

Open Positions

We are actively looking for students to work on several amazing projects that involve:

  • Deep learning-based method for 3D object perception.
  • Visual representation learning for physical interaction (grasping and manipulation).
  • Deep reinforcement and imitation learning-based methods for planning & control.
  • Dual-arm object manipulation.
  • Lifelong Robot learning.
  • Multi-Task multimodal learning.
  • Simulation to real-world transfer learning (Sim2Real).

If you are interested in doing your PhD/Master/Bachelor thesis in one of the mentioned Research Directions, please send us an e-mail including the following information:

  • Short CV
  • Short motivation letter

The motivation letter should state (½ - 1 page):

  • Topics that you are interested in
  • Type of project (theoretical/applied)
  • Intended starting date
  • Your relevant experiences

We will try to get back to you within a week. The primary qualification is interest in doing research, and if you have that, we encourage you to apply even if you have limited experience with AI. We strive to be a diverse and inclusive group that is open to students from all backgrounds.

Seld-funded (externally funded) PhD, Master and Visiting Scholar

Good self-funded PhD, Master, and intern will be considered on a case by case basis. If you are interested in doing your PhD at Interactive Robot Learning Lab and you have funded from your Government (e.g., China Scholarship Council (CSC) scholarship), we can consider your application. Please contact hamidreza.kasaei@rug.nl

Teaching

Academic year 2020/2021:

WMAI003-05: Cognitive Robotics (Coordinator)
WMAI18002: Deep Learning (Lecturer)
KIB.AS03: Autonomous Systems (Lecturer)

Academic year 2019/2020:

KIM.CROB04: Cognitive Robotics (Coordinator)
KIB.AS03: Autonomous Systems (Lecturer)
KIM.ML09: Machine Learning (Assistant)

Contact



Dr. Hamidreza Kasaei
Artificial Intelligence Department,
University of Groningen,
Bernoulliborg building,
Nijenborgh 9 9747 AG Groningen,
The Netherlands.
Office: 340
Tel: +31-50-363-33926
E-mail: hamidreza.kasaei@rug.nl