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Published in 2017 5th RSI International Conference on Robotics and Mechatronics (ICRoM), 2017
Recommended citation: Esfandiari, Mojtaba, Kianoosh Nazari, and Farzam Farahmand. "Robust adaptive bilateral control of teleoperation systems with uncertain parameters and unmodeled dynamics." In 2017 5th RSI International Conference on Robotics and Mechatronics (ICRoM), pp. 95-100. IEEE, 2017.
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Published in 2020 IEEE 16th international conference on automation science and engineering (CASE), 2020
Recommended citation: Parsa, Soran, Disha Kamale, Sariah Mghames, Kiyanoush Nazari, Tommaso Pardi, Aravinda R. Srinivasan, Gerhard Neumann, Marc Hanheide, and Ghalamzan E. Amir. "Haptic-guided shared control grasping: collision-free manipulation." In 2020 IEEE 16th international conference on automation science and engineering (CASE), pp. 1552-1557. IEEE, 2020.
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Published in Software Impacts, 2021
Recommended citation: Ghalamzan, Amir, Kiyanoush Nazari, Hamidreza Hashempour, and Fangxun Zhong. "Deep-LfD: deep robot learning from demonstrations." Software Impacts 9 (2021): 100087.
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Published in 2021 Towards Autonomous Robotic Systems Conference (TAROS), 2021
Recommended citation: Nazari, Kiyanoush, Willow Mandill, Marc Hanheide, and Amir Ghalamzan Esfahani. "Tactile dynamic behaviour prediction based on robot action." In Towards Autonomous Robotic Systems: 22nd Annual Conference, TAROS 2021, Lincoln, UK, September 8–10, 2021, Proceedings 22, pp. 284-293. Springer International Publishing, 2021.
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Published in Robotics: Science and Systems (RSS), 2022
Recommended citation: Mandil, Willow, and Kiyanoush Nazari. "Action conditioned tactile prediction: a case study on slip prediction." Robotics: Science and Systems (2022).
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Published in Proceedings of the AAAI Conference on Artificial Intelligence, 2022
Recommended citation: Sanni, Oluwatoyin, Giorgio Bonvicini, Muhammad Arshad Khan, Pablo C. López-Custodio, and Kiyanoush Nazari. "Deep movement primitives: toward breast cancer examination robot." In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 11, pp. 12126-12134. 2022.
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Published in 6th Annual Conference on Robot Learning (CoRL), 2022
Recommended citation: Nazari, Kiyanoush, Willow Mandil, and Amir Masoud Ghalamzan Esfahani. "Proactive slip control by learned slip model and trajectory adaptation." In Conference on Robot Learning, pp. 751-761. PMLR, 2023.
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Published in Sensors, 2023
Recommended citation: Mandil, Willow, Vishnu Rajendran, Kiyanoush Nazari, and Amir Ghalamzan-Esfahani. "Tactile-sensing technologies: Trends, challenges and outlook in agri-food manipulation." Sensors 23, no. 17 (2023): 7362.
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Published in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
Recommended citation: Nazari, Kiyanoush, Gabriele Gandolfi, Zeynab Talebpour, Vishnu Rajendran, Willow Mandil, Paolo Rocco, and Amir Ghalamzan-E. "Deep functional predictive control (deep-fpc): Robot pushing 3-d cluster using tactile prediction." In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 10771-10776. IEEE, 2023.
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Published in 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024
Recommended citation: Vishnu Rajendran, Willow Mandil, Kiyanoush Nazari, Simon Parsons, and Amir Ghalamzan. "Acoustic soft tactile skin (AST skin)." In 2024 IEEE International Conference on Robotics and Automation (ICRA), pp. 4105-4111. IEEE, 2024.
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Published in 2024 Towards Autonomous Robotic Systems Conference (TAROS), 2024
Recommended citation: Vishnu Rajendran, Kiyanoush Nazari, Simon Parsons, Amir Ghalamzan. "Enabling tactile feedback for robotic strawberry handling using ast skin." In Towards Autonomous Robotic Systems: 25th Annual Conference, TAROS 2024
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Post-graduate course, School of Computer Science, University of Lincoln, 2022
Teaching and lab deomnstration of Probabilistic Movement Primitives with hands-on experiments with robotic manipulation systems.
Workshop, School of Computer Science, University of Lincoln, 2023
Real-robot exprimentation of stabilising an inverted pendulum on a robotic arm’s gripper using tactile feedback.