Dr Naresh Marturi M.S., Ph.D., MIET

Dr Naresh Marturi

Senior Research Scientist in Robotics

Contact details

Email
n.marturi@bham.ac.uk
Address
Extreme Robotics Lab (ERL)
School of Metallurgy and Materials
University of Birmingham
Edgbaston
Birmingham
B15 2TT

Naresh Marturi is an experienced researcher in robotics and machine vision with a demonstrated history of working in the manufacturing industry and higher education. His primary research interests are in the fields of vision-based robotic control (visual servoing), machine vision for industrial robotics and human-robot interaction. In particular, his research concentrates on developing image processing tools for object detection/tracking and integrating them with robust control as well as advanced motion/grasp planning algorithms in order to perform autonomous robotic manipulations with minimal rejection rate. He is driven by a purely scientific desire to solve vision-related advanced robotics problems, as well as the desire to see its broader impact through practical industry-driven applications.

So far, Naresh has (co-)authored over two dozen of high quality research articles in major robotics/computer vision journals and conferences. In this process, he also won a best paper award from IEEE for his contributions on tele-manipulation for nuclear decommissioning. While working as a researcher with one of the world’s leading manufacturer of industrial robots (KUKA AG), Dr Marturi’s media interviews on advanced robotic manipulation appeared in technology magazines such as Automotive World, Food Science, ITV (video report), Eureka Magazine etc.

Qualifications

  • PhD in Automatic Control, France, 2013 (High honours with Jury Felicitations)
  • Master of Science (M.S.) in Computer Technology, Sweden, 2010 (Distinction)
  • Bachelor of Technology (B.Tech.) in Electronics and Control Systems, India, 2006 (Distinction)

Biography

Naresh graduated with Bachelor of Technology (B.Tech.) from JNTU Hyderabad, India in 2006. Before moving to Sweden in 2008, to pursue his masters in robotics, he worked as a lead software developer in India for about two years. He was awarded Master of Science (M.S.) in computer technology from the Orebro University, Sweden in 2010. During his span in Sweden, he worked on many real-time robotics research projects including a summer internship developing an electronic nose (e-nose) device to characterise explosive slam. He led the vision-guided robot localisation team during the integrated project work involving humanoid robot Nao. This was one of the first attempts to integrate such a robot with smart-home technology.

Later, in 2010, Naresh moved to France to work on his PhD thesis entitled “vision and visual servoing for nano-manipulation and nano-characterisation in scanning electron microsocope (SEM)”. His work was one of the first to use electron images for (semi-)automatic robotic applications. During PhD, he developed various computer vision tools and vision-guided robot control strategies for manipulating objects of size less than 10 microns. Due to the important contributions made to micro/nano-robotics community, his PhD thesis has been selected as one of the best PhD theses in the region Franche-Comté (finalist). After being awarded with PhD in automatic control from the University of Franche-Comté in 2013, he worked as a postdoctoral researcher at FEMTO-ST institute, France for a year.

Before joining the Extreme Robotics Laboratory (ERL) as a senior research fellow in robotics in 2018, Naresh worked as a KTP robot vision scientist (funded by the Innovate UK) for three years embedded at KUKA Robotics UK Ltd, one of the worlds’ leading manufacturers of industrial robots. At KUKA, apart from transferring academic knowledge to the industry, and integrating vision systems for automatic control of large industrial robot arms, he was also responsible for developing bespoke multi-dimensional vision-guided techniques for real-time control/motion planning of industrial robots. His work on dynamic object manipulation with human-robot interaction has gained enormous positive feedback from both industry and academia. He was also involved in working closely with companies like Jaguar Land Rover, National Nuclear Lab etc.

Other than research, Dr. Marturi carries 12+ years of real-time cross-platform programming experience in various programming languages. His software application APROS3, which he developed during his PhD, is one of the first nanorobotics software enabling an electron microscope to be used for automatic robotic applications.

Postgraduate supervision

3D pose estimation methodologies for reliable industrial manipulation of complex texture-less objects

Research

  • Robust visual perception for industrial robotics
  • Vision-guided robot motion planning for extreme environments
  • Adaptive robotic grasping with vision/tactile servoing

Other activities

Naresh worked as a freelance research consultant for A.R.M Robotics Ltd. from Aug-Dec 2016, where he led the team developing automatic robot path planning for UK’s nuclear industry to decommission waste in safety-critical radioactive environment. It is the first time in any nuclear plant world-wide; a fully autonomous system has been deployed to perform such challenging tasks.

Publications

International Journals (peer reviewed)

  1. V Ortenzi, N Marturi, M Mistry, J Kuo, R Stolkin, (2018), “A novel control framework capable of detecting contacts and estimating kinematic constraints using vision-based estimates of the robot configuration”, IEEE/ASME Transactions on Mechatronics, in-press. (IF- 4.35)
  2. N Marturi, M Kopicki, A Rastegarpanah, V Rajasekaran, M Adjigble, R Stolkin, A Leonardis, Y Bekiroglu, (2018), “Dynamic grasp and trajectory planning for moving objects”, Autonomous Robots, in-press. (IF - 2.706)
  3. Ma, M., Marturi, N., Li, Y., Leonardis, A., & Stolkin, R. (2018), Region-sequence based six-stream CNN features for general and fine-grained human action recognition in videos, Pattern Recognition, 76: 506-521. (IF - 4.8)
  4. Shen, X., Leandro, L. M., Naresh, M., Yi-Nan, G., Ying, H., (2018) "A Q-learning-based memetic algorithm for multi-objective dynamic software project scheduling." Information Sciences, 428: 1-29. (IF - 4.83)
  5. Alireza, R., Hamid, R., Mozafar, S., Mohammad, R., Naresh, M., Alberto, B., Rui, L., (2018), "Path-planning of a hybrid parallel robot using stiffness and workspace for foot rehabilitation." Advances in Mechanical Engineering 10(1): 1687814017754159. (IF - 0.82)
  6. Ma, M., Marturi, N., Li, Y., Leonardis, A., & Stolkin, R., (2016) “A local-global coupled-layer puppet model for robust online human pose tracking”, In Computer Vision and Image Understanding (CVIU), 153: 163-178. (IF - 2.49)
  7. S Dembélé, O Lehmann, K Medjaher, N Marturi, and N Piat., (2016), “Combining gradient ascent search and support vector machines for effective autofocus of a field emission scanning electron microscope”, In Journal of microscopy, 264(1):79-87. (IF – 1.83)
  8. N Marturi, B Tamadazte, S Dembélé, and N Piat, (2016), “Image-guided nanopositioning scheme for SEM”, In IEEE Transactions on Automation Science and Engineering, 15(1): 45-56. (IF - 3.51)
  9. N Marturi, B Tamadazte, S Dembélé, and N Piat, (2016), "Visual Servoing-Based Depth Estimation Technique for Manipulation inside SEM”, In IEEE Transactions on Instrumentation and Measurement, 65(8): 1847 – 1855. (IF - 2.45)
  10. N Marturi, S Dembélé, and N Piat, (2014), “Scanning electron microscope image signal-to-noise ratio monitoring for micro-nanomanipulation”, In Scanning, 36(4): 419-429, DOI: 10.1002/sca.21137. (IF - 1.91)
  11. A Malti, S Dembélé, N Piat, C Arnoult, N Marturi, (2012), “Toward Fast Calibration of Global Drift in Scanning Electron Microscopes with Respect to Time and Magnification”, In International Journal of Optomechatronics, 6(1): 1-16. (IF - 1.375)
  12. Y Li, G Lu, Y Li, L Jiao, N Marturi, "Using MARS surrogate to tune hyper-parameters of machine learning algorithms". IEEE Transactions on Emerging Topics in Computational Intelligence. (Under review)
  13. Y Li, G Lu, Y Li, L Jiao, N Marturi, “Application of Data Driven Optimization for Change Detection in Synthetic Aperture Radar Images”. Information Sciences. (Under review). (IF - 4.83)

International Conferences (peer reviewed)

  1. M. Adjigble, N. Marturi, V. Ortenzi, V. Rajasekaran, P. Corke, and R. Stolkin, “Model-free and learning-free grasping by Local Contact Moment matching”. IEEE International Conference on Intelligent Robots and Systems (IROS) – under review.
  2. Rastegarpanah, A., Marturi, N., & Stolkin, R. (2017, March). Autonomous vision-guided bi-manual grasping and manipulation. In Advanced Robotics and its Social Impacts (ARSO), pp. 1-7). IEEE.
  3. 3.      N Marturi, A Rastegarpanah, C Takahashi, Y Bekiroglu, J Kuo, R Stolkin, “Towards advanced robotic manipulation for nuclear decommissioning: a pilot study on teleoperation and autonomy”, In IEEE International Conference on Robotics and Automation for Humanitarian Applications, pp. 1-8. 2016. (Best Paper Award)
  4. V Ortenzi, N Marturi, R Stolkin, J Kuo, M Mistry, “Vision-guided state estimation and control of robotic manipulators which lack proprioceptive sensors”, In IEEE International Conference on Intelligent Robots and Systems (IROS), pp. 3567-3574. 2016.
  5. N Marturi, V Ortenzi, J Xiao, M Adjigble, R Stolkin, A Leonardis. “A real-time tracking and optimised gaze control for a redundant humanoid robot head.” In IEEE-RAS International Conference on Humanoid Robots, pp. 467-474. 2015.
  6. L Cui, N Marturi, E Marchand, S Dembélé, N Piat. “Closed-Loop Autofocus Scheme for Scanning Electron Microscope” In ISOT- MATEC Web of Conferences, vol. 32. 2015.
  7. N Marturi, B Tamadazte, S Dembélé, N Piat, “Visual Servoing Schemes for Automatic Nanopositioning in Scanning Electron Microscope”, In IEEE International Conference on Robotics and Automation (ICRA), pp. 981-986, 2014.
  8. N Marturi, S Dembélé, N Piat, “Depth and Shape Estimation from Focus in Scanning Electron Microscope for Micromanipulation”, In IEEE International Conference on Control, Automation, Robotics and Embedded systems (CARE), pp. 1-6. 2013.
  9. N Marturi, B Tamadazte, S Dembélé, and N Piat, “Visual Servoing-Based Approach for Efficient Autofocusing in Scanning Electron Microscope”, In IEEE International Conference on Intelligent Robots and Systems (IROS), pp. 2677-2682, 2013.
  10. N Marturi, S Dembélé, N Piat, “Fast Image Drift Compensation in Scanning Electron Microscope Using Image Registration”, In IEEE International Conference on Automation Science and Engineering (CASE), pp. 807-812, 2013.
  11. N Marturi, S Dembélé, N Piat, “Performance evaluation of scanning electron microscopes using signal-to-noise ratio”, In International Workshop on MicroFactories (IWMF), pp. 1-6, 2012.
  12. S Dembélé, N Piat, N Marturi, B Tamadazte, “Gluing free assembly of an advanced 3D structure using visual servoing”, In Proceedings of the Micromechanics and Microsystems Europe Workshop (MME), Germany, 2012.
  13. A Louloudi, A Mosallam, N Marturi, P Janse, V Hernandez, “Integration of the Humanoid Robot Nao inside a Smart Home: A Case Study”, In Proceedings of the Swedish AI Society Workshop (SAIS), 18, pp. 35-44. Uppsala, Sweden, 2010.

Book Chapters and Monographs

  1. Marturi, Naresh, Alireza Rastegarpanah, Vijaykumar Rajasekaran, Valerio Ortenzi, Yasemin Bekiroglu, Jeffrey Kuo, and Rustam Stolkin. "Towards Advanced Robotic Manipulations for Nuclear Decommissioning." In Robots Operating in Hazardous Environments. InTech, 2017.
  2. Naresh Marturi, “Vison and visual servoing for nanomanipulation and nanocharacterization using scanning electron microscope”, Ph.D. Thesis report, Université de Franche-Comté, Besançon. 2013.
  3. Naresh Marturi, “Vision Based Grasp Planning for Robot Assembly”, International Master’s Thesis, Örebro University. 2010.

Press and media appearances

  1. Manufacturing the future: robots learn food handling. Food Science and Technology. February 2017 edition. URL: http://tinyurl.com/y7es2bnq
  2. Special report: Artificial intelligence and the auto industry. Automotive world. March 2017. URL: http://tinyurl.com/y977njjr
  3. Report on AI for industrial manufacturing. Eureka Magazine. in-press.