Muhayy Ud Din
KU Center for Autonomous Robotic Systems - Khalifa University, UAE.
Email: muhayyuddin_1@hotmail.com
Blogs: https://muhayyuddin.github.io/blogs/index.html
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Google scholar
Current research interest
My current research interest is to bring the robots out of the labs and make them capable of performing the manipulation tasks in a robust and intelligent way. Robots should not scare or hesitate to interact with the environment :-)
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Navigation and manipulation in marine environment using unmanned surface vessels to perform the task such as environmental monitoring and autonomous surveillance for maritime security, rescue operations and for the irregular activity detection of vessels around ports.
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My strength
I don't have any comfort zone. I can quickly adapt myself to any new set of tools for handling challenging problems.
Biography
I received the BS(Hons.) degree in Computational Physics from the University of the Punjab, in 2008 and MS degree in Computer Science from the GC University Lahore, Pakistan in 2011. I worked as Lecturer at the Department of Computer Science of the GC University (2011 to 2012). In the GC University, I was also attached to the Cybernetic Intelligence Research Lab (CIRL) and involved in projects related to Cognitive Robotics and Quantum Artificial Intelligence. After that, I joined the Centre for High Energy Physics (CHEP) as a visiting faculty member and engaged in teaching computational Physics related courses. I did my Ph.D. in Automatic Control, Robotics and Computer Vision from Institute of Industrial and Control Engineering (IOC), Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
During my PhD, I also participated as a researcher in R&D projects of Spanish and Catalonian Governments. Moreover, I visited other research labs (Kavraki Lab, RICE University, USA and Institute of Robotics and Mechatronics, German Aerospace Center) as a short-term research scholar.
My Ph.D. thesis is about “Physics-based Motion Planning for Grasping and Manipulation”. I developed Knowledge-oriented Physics-based motion planning approaches. These strategies use knowledge-based reasoning process to guide the physics-based motion planner for navigating among moveable obstacles (some related videos: https://goo.gl/KNYKNC and https://goo.gl/GJpXqM ). Moreover, I proposed physics-based motion planning approaches for grasping in clutter and uncertain environment (some related videos are: https://goo.gl/RzLVi1, https://goo.gl/ZorqCF, and https://goo.gl/bHspjZ ) and motion planning with temporal goals for mobile robots (a related video: https://goo.gl/tGRuRg ). Beside simulation environment. I have practical experience to work with real robots: ABB YuMi, KUKA-LWR, PAL-TiAGo, and UR5.
After my PhD in 2019, I joined ITK System Engineering (BOSCH Group of Companies) as research and development engineer. I was involve in the projects related to Medical Robotics, Augmented Reality, and Software Testing. I worked at this position for three year.
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Research Areas
- Marine robotics
- Robotic software development
- Physics-based motion planning for manipulation
- Grasping and manipulation
- Knowledge-oriented task and motion planning
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Recent Results
Field testing for The Mohamed Bin Zayed International Robotics Challenge (MBZIRC)- maritime grand challenge
Planning motions to grasp an object in cluttered and uncertain environments is a challenging task, particularly when a collision-free trajectory does not exist and objects obstructing the way are required to be carefully grasped and moved out. This paper takes a different approach and proposes to address this problem by using a randomized physics-based motion planner that permits robot-object and object-object interactions. The main idea is to avoid an explicit high-level reasoning of the task by providing the motion planner with a physics engine to evaluate possible complex multi-body dynamical interactions.