Nikhil
Also known as: Nikhil Deshpande
University of Nottingham, Istituto Italiano di Tecnologia, North Carolina State University
About
I am an Associate Professor in Robotics and AI at the University of Nottingham, UK. I am a deputy leader of the CHART research group (https://www.chartresearch.org/). My main research thrusts are around robotics and AI for chemistry automation (self-driving labs), and assistive robotics for neurorehabilitation.
Previously, I was a Researcher in the Advanced Robotics research line, leading the VICARIOS group, to develop novel, mixed reality user interfaces for advanced robotic teleoperation systems. I was leading the "SISTEMI CIBERNETICI COLLABORATIVI - TELEOPERAZIONE" project, which will create next-generation, collaborative teleoperation systems for intuitive operation in hazard-prone environments and industry. Specifically, the objectives are the development and integration of technologies including: (i) novel hydraulic quadruped field robot; (ii) new dexterous robotic manipulator arm; (iii) novel master hand exoskeleton haptic device; and (iv) new user interaction interfaces with augmented and virtual reality systems.
My previous research focused on the design and development of robot-assisted surgical tools for microsurgery, particularly, transoral laser microsurgery. The research also involved holistic design, development, and assessment of novel devices and intuitive user interfaces for robot-assisted technologies using GUI software, computer vision techniques, and human factors and usability studies. My research background is in distributed wireless sensing, autonomous navigation, sensor fusion, mechanical design, and user interface development.
Originally from Pune, India, I graduated with a Bachelors in Electrical Engineering from the Government College of Engineering (COEP), in 2003. The bug to tinker with robots led me to an applications engineering position with Rockwell Automation India Ltd., in New Delhi, India, which introduced me to the basics of plant automation and industrial robots for manufacturing processes and automobile assembly lines. The curiosity to design robots and improve them got me to pursue graduate studies in USA.
Beginning with my Master’s in Integrated Manufacturing Systems Engineering at North Carolina State University (NCSU) in 2005, I got the opportunity to design and program mobile robots, and work on state-of-the-art technologies including wireless sensor networks. Here, under the guidance of Prof. Steve Jackson, I developed a smart-home automation solution for in-situ wall-moisture sensing using low-power WSNs. Subsequently, I joined the Center for Robotics and Intelligent Machines (CRIM) at NCSU to continue on for my PhD in Electrical Engineering with Prof. Edward Grant. My dissertation was on sensor-network assisted mobile robot navigation.
In the summer of 2011, I interned at the Robert Bosch Robotics Research Center in California, working manipulator state estimation using low cost sensing technology - accelerometers and gyroscopes. I collaborated with the Stanford Biorobotics group (Prof. Kenneth Salisbury) and adapted my solution for the PR2 robot arm as well as the new low-cost Stanford Arm.
Employment
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University of Nottingham Associate Professor2024 - Present
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Istituto Italiano di Tecnologia Researcher2012 - 2023
Education
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North Carolina State University PhD2007 - 2012
Projects & Funding
Projects & funding information is unavailable.
Publications (42)
- Designing Intuitive Human–Drone Interfaces for Post‑disaster Response Save
- Towards an Immersive Digital Twin Based Robotic Inspection Framework for Confined Spaces Save
- A Multimodal Adaptive Framework for Social Interaction with the MiRo-E Robot Save
- Learning Skills From Demonstrations: A Trend From Motion Primitives to Experience Abstraction Save
- Towards Gaze-contingent Visualization of Real-time 3D Reconstructed Remote Scenes in Mixed Reality Save
- Analysing Gyroscopic Balance Support in Full-Body Human Models Based on Predictive Simulations Save
- Real-time Immersive Remote Telerobotics: Highlighting the Benefit of Humans in the Loop and Applying Machine Learning Save
- A Perception-Driven Approach To Immersive Remote Telerobotics Save
- Learning Skills from Demonstrations: A Trend from Motion Primitives to Experience Abstraction Save
- Spatial Augmented Respiratory Cardiofeedback Design for Prosthetic Embodiment Training: a Pilot Study Save