People
Current people in the Ocean Systems Lab
Academics
Prof. Yvan Petillot | Personal page
Full Professor of Robotics and Computer Vision at Heriot-Watt University. He is a leading member of the Oceans Systems Laboratory, the deputy director of the Institute for Sensor Signals and Systems and the deputy director of the joint research institute in Signal and Image Processing (ERP-SIP) with Edinburgh University. He is also currently a Royal Society Industry Fellow in collaboration with SeeByte Ltd, a company he co-founded in 2001 and in which he was Chief Technical Officer until 2010.
Full Professor of Robotics and Computer Vision at Heriot-Watt University. He is a leading member of the Oceans Systems Laboratory, the deputy director of the Institute for Sensor Signals and Systems and the deputy director of the joint research institute in Signal and Image Processing (ERP-SIP) with Edinburgh University. He is also currently a Royal Society Industry Fellow in collaboration with SeeByte Ltd, a company he co-founded in 2001 and in which he was Chief Technical Officer until 2010.
Dr. Ignacio Carlucho | Personal page
He is currently an Assistant Professor in Robotics, Computer Vision and Autonomous Systems at Heriot-Watt University. His research focuses on the development of intelligent robots that can perform complex tasks in real-world environments. Particularly, he is interested in robots that can cooperate with other agents. He obtained his PhD in 2019 from the National University of Central Buenos Aires, Argentina. He was previously a postdoctoral researcher at Louisiana State University, USA, from 2020 to 2021. He then held a position as a postdoctoral researcher at the University of Edinburgh, from 2021 to 2023.
He is currently an Assistant Professor in Robotics, Computer Vision and Autonomous Systems at Heriot-Watt University. His research focuses on the development of intelligent robots that can perform complex tasks in real-world environments. Particularly, he is interested in robots that can cooperate with other agents. He obtained his PhD in 2019 from the National University of Central Buenos Aires, Argentina. He was previously a postdoctoral researcher at Louisiana State University, USA, from 2020 to 2021. He then held a position as a postdoctoral researcher at the University of Edinburgh, from 2021 to 2023.
Dr. Maria Koskinopoulou | Personal page
She is currently an Assistant Professor in Robotics and Computer Vision at the Institute of Signals, Sensors and Systems (ISSS), of the School of Engineering & Physical Sciences (EPS), of Heriot-Watt University, Edinburgh, UK. She holds a BSc in Electrical and Computer Engineering, MSc in Computational Neuroscience and PhD in Computer Science. Her interests and expertise are in the areas of Computer Vision and Machine (Deep) Learning, Robotic Manipulation and Smart Medical Devices. She was recently a Post-Doctoral Research Fellow at the Biomedical Robotics Laboratory, of Advanced Robotics Department of the Italian Institute of Technology (IIT), focusing on robotic manipulators and sensory systems applied to surgical scenarios while designing and developing smart medical devices for both intravenous catheterization processes and cancer tissue identification. She has considerable experience in large RTD projects that regards integrated robotics systems. Up to now, she has been involved in various projects related to robotic arms and the relevant object manipulations via those arms, working, at the same time, on the core of Human-Robot Interaction, Vision-guided Systems for Abnormal Tissue Detection, AI algorithms for Industrial Robotic Applications, Machine Learning, Neural Networks and Deep Learning technologies.
She is currently an Assistant Professor in Robotics and Computer Vision at the Institute of Signals, Sensors and Systems (ISSS), of the School of Engineering & Physical Sciences (EPS), of Heriot-Watt University, Edinburgh, UK. She holds a BSc in Electrical and Computer Engineering, MSc in Computational Neuroscience and PhD in Computer Science. Her interests and expertise are in the areas of Computer Vision and Machine (Deep) Learning, Robotic Manipulation and Smart Medical Devices. She was recently a Post-Doctoral Research Fellow at the Biomedical Robotics Laboratory, of Advanced Robotics Department of the Italian Institute of Technology (IIT), focusing on robotic manipulators and sensory systems applied to surgical scenarios while designing and developing smart medical devices for both intravenous catheterization processes and cancer tissue identification. She has considerable experience in large RTD projects that regards integrated robotics systems. Up to now, she has been involved in various projects related to robotic arms and the relevant object manipulations via those arms, working, at the same time, on the core of Human-Robot Interaction, Vision-guided Systems for Abnormal Tissue Detection, AI algorithms for Industrial Robotic Applications, Machine Learning, Neural Networks and Deep Learning technologies.
Postdocs
Dr. Markus Buchholz | Personal page
Markus is a software and robotics professional with a Ph.D. in Mechatronics. With over 20 years of experience, he has dedicated his career to the intricate nuances of robotics and its advancements.Currently, Markus's research is centered on motion planning and manipulation in underwater robotics. His expertise in this niche area showcases his commitment to pushing the boundaries of what's possible in the field. Beyond his academic contributions, Markus's expertise has led to the development of cutting-edge technologies and methodologies. His innovative approach has been recognized with two patents in robotics.
Markus is a software and robotics professional with a Ph.D. in Mechatronics. With over 20 years of experience, he has dedicated his career to the intricate nuances of robotics and its advancements.Currently, Markus's research is centered on motion planning and manipulation in underwater robotics. His expertise in this niche area showcases his commitment to pushing the boundaries of what's possible in the field. Beyond his academic contributions, Markus's expertise has led to the development of cutting-edge technologies and methodologies. His innovative approach has been recognized with two patents in robotics.
Dr. Vibhav Bharti | Personal page
Project description: It is of importance to oil and gas industry to inspect the pipelines laid down underwater for maintainance. Human efforts are not only expensive and time consuming but also there exists a chance of hazard and danger to human divers working on such tasks. Autonomous Underwater Vehicles and Remotely Operated Vehicles have shown major involvment in improving the quality of inspection over last couple of decades and reduction in human efforts. However, there are still challenges to be addressed. One such challenge that needs to be addressed is to track pipelines in and out of burial in an efficient manner. This project will investigate statistical methods to keep track of target(pipelines) using multiple sensors. Data from these sensors will be incorporated in statistical multi-sensor fusion framework using Probability Hypothesis Density (PHD) filter for having better estimates of state of the target(s).
Project description: It is of importance to oil and gas industry to inspect the pipelines laid down underwater for maintainance. Human efforts are not only expensive and time consuming but also there exists a chance of hazard and danger to human divers working on such tasks. Autonomous Underwater Vehicles and Remotely Operated Vehicles have shown major involvment in improving the quality of inspection over last couple of decades and reduction in human efforts. However, there are still challenges to be addressed. One such challenge that needs to be addressed is to track pipelines in and out of burial in an efficient manner. This project will investigate statistical methods to keep track of target(pipelines) using multiple sensors. Data from these sensors will be incorporated in statistical multi-sensor fusion framework using Probability Hypothesis Density (PHD) filter for having better estimates of state of the target(s).
PhD candidates
Pierre Nicolay | Personal page
Project title: Lifelong Learning for Vision based AUV Control
The main objective is to design a low-level controller for autonomous underwater vehicles (AUVs) using learning frameworks. The algorithm should be portable across multiple robots. The controller should adapt quickly to any change in the dynamics (e.g. increase of payload, current disturbances or thruster efficiency decay)
Project title: Lifelong Learning for Vision based AUV Control
The main objective is to design a low-level controller for autonomous underwater vehicles (AUVs) using learning frameworks. The algorithm should be portable across multiple robots. The controller should adapt quickly to any change in the dynamics (e.g. increase of payload, current disturbances or thruster efficiency decay)
Ellis Niamh | Personal page
Project title: Digital Twin for Safety: Underwater semi-autonomous inspection
Project title: Digital Twin for Safety: Underwater semi-autonomous inspection
Zebin Huang | Personal page
Project title: Assured Underwater Data Acquisition
Education: MSc in Human and Biological Robotics, Imperial College London, 2021;
BEng in Ocean Technology & BEng in Computer Science and Technology, Dalian University of Technology, 2020
Research interests: robotics, reinforcement learning, and human-machine interaction
Project title: Assured Underwater Data Acquisition
Education: MSc in Human and Biological Robotics, Imperial College London, 2021;
BEng in Ocean Technology & BEng in Computer Science and Technology, Dalian University of Technology, 2020
Research interests: robotics, reinforcement learning, and human-machine interaction
Michele Grimaldi | Personal page
Project title: Underwater inspection and planning for robust scene identification and advanced manipulation
Project title: Underwater inspection and planning for robust scene identification and advanced manipulation
Adip Das | Personal page
Project title: Dual-robot manipulation in industrial settings for assembly and disassembly electronic equipment and coordinated actions between human workers and robotic agents using machine learning.
Project description: This thesis addresses the understudied aspects of robotic assembly and disassembly in the context of the Fourth Industrial Revolution. The focus is on developing a fully autonomous system capable of efficiently performing assembly and disassembly tasks, considering the entire chain from design to reassembly. The main objective is to enhance the speed and affordability of production by implementing a vision-based robotic system for electronic equipment assembly/disassembly in industrial setups. The research aims to address uncertainties in end-of-life products without prior product-specific knowledge and explores the potential of physical human-robot collaboration in achieving economic feasibility. The project utilizes technologies for dual-robot manipulation, physical interaction, and machine-learning algorithms.
Project title: Dual-robot manipulation in industrial settings for assembly and disassembly electronic equipment and coordinated actions between human workers and robotic agents using machine learning.
Project description: This thesis addresses the understudied aspects of robotic assembly and disassembly in the context of the Fourth Industrial Revolution. The focus is on developing a fully autonomous system capable of efficiently performing assembly and disassembly tasks, considering the entire chain from design to reassembly. The main objective is to enhance the speed and affordability of production by implementing a vision-based robotic system for electronic equipment assembly/disassembly in industrial setups. The research aims to address uncertainties in end-of-life products without prior product-specific knowledge and explores the potential of physical human-robot collaboration in achieving economic feasibility. The project utilizes technologies for dual-robot manipulation, physical interaction, and machine-learning algorithms.
Sümer Tunçay | Personal page</a>
Project title: Towards collaborative inspections with multi-agent robotic systems via reinforcement learning.
Project title: Towards collaborative inspections with multi-agent robotic systems via reinforcement learning.
Favour Adetunji | Personal page</a>
Project title: Cable and pipe tracking for underwater autonomous vehicles.
Project title: Cable and pipe tracking for underwater autonomous vehicles.
Master students
Michael Kirby
Supervisors: Dr. Maria Koskinopoulou and Dr. Ignacio Carlucho
Project title: Vision-based Navigation and Planning of Underwater Vehicles
Supervisors: Dr. Maria Koskinopoulou and Dr. Ignacio Carlucho
Project title: Vision-based Navigation and Planning of Underwater Vehicles