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Dr Lorenzo Jamone

Lorenzo

Senior Lecturer in Robotics

Email: l.jamone@qmul.ac.uk
Telephone: +44 20 7882 7825
Room Number: Peter Landin, CS 407
Website: http://lorejam.blogspot.co.uk/

Teaching

Advanced Robotics Systems (Robotics III) (Undergraduate)

The module will build on previous knowledge acquired in the previous years on the programme and also introduce new and advanced concept related to geometric, kinematic, and dynamic robots manipulation, vision and machine learning specifically for Robotics, motion control and practical implementation of locomotion solutions, mechanical considerations of medical robots and the necessity of understanding acceptance and ethical values, etc. It will introduce the practicality of applying multidisciplinary techniques in enhancing the current state of the art in Robotics Engineering and allow the students to explore creative and engineered solutions that are outside the box along side conventional industrial and cognitive applications.

Advanced Robotics Systems (Robotics III) (Postgraduate)

The module will introduce both basic and advanced concepts related to geometric, kinematic, and dynamic robots manipulation, vision and machine learning specifically for Robotics, motion control and practical implementation of locomotion solutions, mechanical considerations of medical robots and the necessity of understanding acceptance and ethical values, etc. It will introduce the practicality of applying multidisciplinary techniques in enhancing the current state of the art in Robotics and allow the students to explore creative and engineered solutions that are outside the box along side conventional industrial and cognitive applications.

Cognitive Robotics (Postgraduate)

This module addresses the emerging field of autonomous systems possessing artificial reasoning skills and also environment and context awareness. The module will introduce students to advance numerical and computational techniques associated with machine learning and artificial intelligence. Successfully-applied algorithms and autonomy models form the basis for study, and provide students an opportunity to design such a system as part of their coursework project. Theory and practical applications will be linked through discussion of real systems such as medical robotic surgeons and robotic musicians.

Cognitive Robotics (Robotics IV) (Undergraduate)

This module addresses the emerging field of autonomous systems possessing artificial reasoning skills and also environment and context awareness. The module will introduce students to advance numerical and computational techniques associated with machine learning and artificial intelligence. Successfully-applied algorithms and autonomy models form the basis for study, and provide students an opportunity to design such a system as part of their coursework project. Theory and practical applications will be linked through discussion of real systems such as the medical robotic surgeons and robotic musicians.

Research

Research Interests:

I am Lecturer in Robotics and Director of the CRISP group at the School of Electronic Engineering and Computer Science (EECS) of the Queen Mary University of London (QMUL). The CRISP group is part of ARQ (Advanced Robotics at Queen Mary).
Since October 2018, I am also Turing Fellow at The Alan Turing Institute.

My main interest is in Cognitive Robotics: building intelligent robots by taking inspiration from humans, and validating theories of human cognition by testing computational models on robots.
Topics include: dexterous manipulation, visuo-haptic perception and exploration, object affordances, tool use, body schema, eye-hand coordination, human-robot interaction and collaboration, tactile and force sensing.

I also collaborate with VisLab, at the Instituto de Sistemas e Robotica of the Instituto Superior Tecnico (Lisbon, Portugal), as visiting associate researcher in humanoid and cognitive robotics, and with SuganoLab, at the Department of Modern Mechanical Engineering of Waseda University (Tokyo, Japan), as visiting professor in tactile sensing for robotic manipulation.

Before I was with the Biped Group of Takanishi Lab (Waseda University), and with the RBCS (Robotics Brain and Cognitive Science) Department of the IIT (Italian Institute of Technology). 

Publications

    • Kirby E, Zenha R, Jamone L (2022), Comparing Single Touch to Dynamic Exploratory Procedures for Robotic Tactile Object Recognition $nameOfConference


    • Taniguchi T, Nagai T, Shimoda S et al. (2022), Special issue on symbol emergence in robotics and cognitive systems (II) $nameOfConference


    • Dehban A, Zhang S, Cauli N et al. (2022), Learning Deep Features for Robotic Inference from Physical Interactions $nameOfConference


    • Taniguchi T, Nagai T, Shimoda S et al. (2022), Special issue on Symbol Emergence in Robotics and Cognitive Systems (I) $nameOfConference


    • Shimoda S, Jamone L, Ognibene D et al. (2021), What is the role of the next generation of cognitive robotics? $nameOfConference


    • Vitanov I, Farkhatdinov I, Denoun B et al. (2021), A Suite of Robotic Solutions for Nuclear Waste Decommissioning $nameOfConference


    • Ozkan EE, Gurion T, Hough J et al. (2021), Specific hand motion patterns correlate to miscommunications during dyadic conversations $nameOfConference


    • Slonina Z, Bonzini AA, Brown J et al. (2021), Using RoboChick to Identify the Behavioral Features Promoting Social Interactions 2021 IEEE International Conference on Development and Learning (ICDL)


    • Siddiqui MS, Coppola C, Solak G et al. (2021), Grasp Stability Prediction for a Dexterous Robotic Hand Combining Depth Vision and Haptic Bayesian Exploration $nameOfConference


    • Neto M, Ribeiro P, Nunes R et al. (2021), A soft tactile sensor based on magnetics and hybrid flexible-rigid electronics $nameOfConference


    • Denoun B, Leon B, Hansard M et al. (2021), Grasping Robot Integration and Prototyping: The GRIP Software Framework $nameOfConference


    • Siddiqui MS, Coppola C, Solak G et al. (2021), Discovering Stable Robot Grasps for Unknown Objects in Presence of Uncertainty Using Bayesian Models $nameOfConference


    • Zenha R, Denoun B, Coppola C et al. (2021), Tactile Slip Detection in the Wild Leveraging Distributed Sensing of both Normal and Shear Forces $nameOfConference


    • Ribeiro P, Cardoso S, Bernardino A et al. (2020), Fruit quality control by surface analysis using a bio-inspired soft tactile sensor $nameOfConference


    • Omarali B, Denoun B, Althoefer K et al. (2020), Virtual Reality based Telerobotics Framework with Depth Cameras $nameOfConference


    • Frazier PA, Jamone L, Althoefer K et al. (2020), Plant Bioinspired Ecological Robotics $nameOfConference


    • Hoffmann M, Lanillos P, Jamone L et al. (2020), Editorial: Body Representations, Peripersonal Space, and the Self: Humans, Animals, Robots $nameOfConference


    • Ribeiro P, Cardoso S, Bernardino A et al. (2020), Highly sensitive bio-inspired sensor for fine surface exploration and characterization $nameOfConference


    • Junput B, Farkhatdinov I, Jamone L (2020), Touch It, Rub It, Feel It! Haptic Rendering of Physical Textures with a Low Cost Wearable System $nameOfConference


    • Taniguchi T, Piater J, Worgotter F et al. (2019), Symbol Emergence in Cognitive Developmental Systems: A Survey $nameOfConference


    • Solak G, Jamone L (2019), Learning by Demonstration and Robust Control of Dexterous In-Hand Robotic Manipulation Skills $nameOfConference


    • Saponaro G, JAMONE L, Alexandre B et al. (2019), Beyond the Self: Using Grounded Affordances to Interpret and Describe Others’ Actions $nameOfConference


    • Junput B, Wei X, Jamone L (2019), Feel It on Your Fingers: Dataglove with Vibrotactile Feedback for Virtual Reality and Telerobotics $nameOfConference


    • Holgado AC, Alvarez Lopez JA, Schmitz A et al. (2018), An Adjustable Force Sensitive Sensor with an Electromagnet for a Soft, Distributed, Digital 3-axis Skin Sensor $nameOfConference


    • Castanheira J, Vicente P, Martinez-Cantin R et al. (2018), Finding safe 3D robot grasps through efficient haptic exploration with unscented Bayesian optimization and collision penalty $nameOfConference


    • Vallverdú J, Trovato G, Jamone L (2018), Allocentric emotional affordances in HRI: The multimodal binding $nameOfConference


    • Schydlo P, Rakovic M, Jamone L et al. (2018), Anticipation in Human-Robot Cooperation: A Recurrent Neural Network Approach for Multiple Action Sequences Prediction $nameOfConference


    • Zenha R, Vicente P, Jamone L et al. (2018), Incremental adaptation of a robot body schema based on touch events $nameOfConference


    • HOUGH J, JAMONE L, Schlangen D et al. (2018), Towards a Types-As-Classifiers Approach to Dialogue Processing in Human-Robot Interaction Workshop on Dialogue and Perception (DaP 2018)

    • Antunes A, Saponaro G, Morse A et al. (2018), Learn, plan, remember: A developmental robot architecture for task solving $nameOfConference


    • Saponaro G, Vicente P, Dehban A et al. (2018), Learning at the ends: From hand to tool affordances in humanoid robots $nameOfConference


    • Tomo TP, Regoli M, Schmitz A et al. (2018), A New Silicone Structure for uSkin—A Soft, Distributed, Digital 3-Axis Skin Sensor and Its Integration on the Humanoid Robot iCub $nameOfConference


    • Jamone L, Ugur E, Cangelosi A et al. (2018), Affordances in Psychology, Neuroscience, and Robotics: A Survey $nameOfConference


    • Jamone L, Ugur E, Santos-Victor J (2018), Guest Editorial Special Issue on Affordances $nameOfConference


    • Vicente P, Jamone L, Bernardino A (2018), Markerless Eye-Hand kinematic calibration on the iCub humanoid robot $nameOfConference


    • Dehban A, Jamone L, Kampff AR et al. (2017), A deep probabilistic framework for heterogeneous self-supervised learning of affordances $nameOfConference


    • Ribeiro P, Khan MA, Alfadhel A et al. (2017), A Miniaturized Force Sensor Based on Hair-Like Flexible Magnetized Cylinders Deposited over a Giant Magnetoresistive Sensor $nameOfConference


    • Saponaro G, Jamone L, Bernardino A et al. (2017), Interactive Robot Learning of Gestures, Language and Affordances GLU 2017 International Workshop on Grounding Language Understanding


    • Ribeiro PM, Alfhadel A, Kosel J et al. (2017), A miniaturized force sensor based on hair-like flexible magnetized cylinders deposited over a giant magnetoresistive sensor $nameOfConference


    • JAMONE L (2017), Covering a Robot Fingertip with uSkin: a Soft Electronic Skin with Distributed 3-axis Force Sensitive Elements for Robot Hands $nameOfConference


    • Paulino T, Ribeiro P, Neto M et al. (2017), Low-cost 3-axis soft tactile sensors for the human-friendly robot Vizzy $nameOfConference


    • Vicente P, Jamone L, Bernardino A (2017), Towards markerless visual servoing of grasping tasks for humanoid robots $nameOfConference


    • Ribeiro P, Asadullah Khan M, Alfadhel A et al. (2017), Bioinspired Ciliary Force Sensor for Robotic Platforms $nameOfConference


    • Saponaro G, Vicente P, Dehban A et al. (2017), Learning at the Ends: From Hand to Tool Affordances in Humanoid Robots $nameOfConference

    • Tomo TP, Wong WK, Schmitz A et al. (2016), A modular, distributed, soft, 3-axis sensor system for robot hands $nameOfConference


    • Nogueira J, Martinez-Cantin R, Bernardino A et al. (2016), Unscented Bayesian optimization for safe robot grasping $nameOfConference


    • Vicente P, Jamone L, Bernardino A (2016), Robotic Hand Pose Estimation Based on Stereo Vision and GPU-enabled Internal Graphical Simulation $nameOfConference


    • Dehban A, Jamone L, Kampff AR et al. (2016), Denoising auto-encoders for learning of objects and tools affordances in continuous space $nameOfConference


    • Antunes A, Jamone L, Saponaro G et al. (2016), From human instructions to robot actions: Formulation of goals, affordances and probabilistic planning $nameOfConference


    • Tomo TP, Somlor S, Schmitz A et al. (2016), Design and Characterization of a Three-Axis Hall Effect-Based Soft Skin Sensor. $nameOfConference


    • Vicente P, Jamone L, Bernardino A (2016), Online body schema adaptation based on internal mental simulation and multisensory feedback $nameOfConference


    • Jamone L, Bernardino A, Santos-Victor J (2016), Benchmarking the Grasping Capabilities of the iCub Hand with the YCB Object and Model Set $nameOfConference


    • Tomo TP, Somlor S, Schmitz A et al. (2015), Development of a hall-effect based skin sensor $nameOfConference


    • Jamone L, Natale L, Metta G et al. (2015), Highly sensitive soft tactile sensors for an anthropomorphic robotic hand $nameOfConference


    • Cardoso C, Jamone L, Bernardino A (2015), A novel approach to dynamic movement imitation based on quadratic programming $nameOfConference


    • Vicente P, Ferreira R, Jamone L et al. (2015), GPU-enabled particle based optimization for robotic-hand pose estimation and self-calibration $nameOfConference


    • Brandão M, Jamone L, Kryczka P et al. (2015), Reaching for the unreachable: Integration of locomotion and whole-body movements for extended visually guided reaching $nameOfConference


    • Jamone L, Saponaro G, Antunes A et al. (2015), Learning object affordances for tool use and problem solving in cognitive robots $nameOfConference

    • Vicente P, Ferreira R, Jamone L et al. (2014), Eye-hand online adaptation during reaching tasks in a humanoid robot $nameOfConference


    • Goncalves A, Abrantes J, Saponaro G et al. (2014), Learning intermediate object affordances: Towards the development of a tool concept $nameOfConference


    • Jamone L, Fumagalli M, Natale L et al. (2014), Control of physical interaction through tactile and force sensing during visually guided reaching $nameOfConference


    • Jamone L, Damas B, Santos-Victor J (2014), Incremental learning of context-dependent dynamic internal models for robot control $nameOfConference


    • Jamone L, Brandao M, Natale L et al. (2014), Autonomous online generation of a motor representation of the workspace for intelligent whole-body reaching $nameOfConference


    • Gonçalves A, Saponaro G, Jamone L et al. (2014), Learning visual affordances of objects and tools through autonomous robot exploration $nameOfConference


    • Trovato G, Zecca M, Sessa S et al. (2013), Towards culture-specific robot customisation: A study on greeting interaction with Egyptians $nameOfConference


    • Trovato G, Zecca M, Sessa S et al. (2013), Cross-cultural study on human-robot greeting interaction: acceptance and discomfort by Egyptians and Japanese $nameOfConference


    • Damas B, Jamone L, Santos-Victor J (2013), Open and closed-loop task space trajectory control of redundant robots using learned models $nameOfConference


    • Kishi T, Kojima T, Endo N et al. (2013), Impression survey of the emotion expression humanoid robot with mental model based dynamic emotions $nameOfConference


    • Otani T, Iizuka A, Takamoto D et al. (2013), New shank mechanism for humanoid robot mimicking human-like walking in horizontal and frontal plane $nameOfConference


    • Jamone L, Damas B, Santos-Victor J et al. (2013), Online learning of humanoid robot kinematics under switching tools contexts $nameOfConference


    • Jamone L, Natale L, Sandini G et al. (2012), Interactive online learning of the kinematic workspace of a humanoid robot $nameOfConference


    • Jamone L, Natale L, Hashimoto K et al. (2012), Learning the reachable space of a humanoid robot: A bio-inspired approach $nameOfConference


    • Jamone L, Natale L, Nori F et al. (2012), Autonomous online learning of reaching behavior in a humanoid robot $nameOfConference


    • Jamone L, Damas B, Endo N et al. (2012), Incremental Development of Multiple Tool Models for Robotic Reaching Through Autonomous Exploration $nameOfConference


    • Jamone L, Natale L, Hashimoto K et al. (2011), Learning task space control through goal directed exploration $nameOfConference


    • Jamone L, Fumagalli M, Metta G et al. (2010), Machine-learning based control of a human-like tendon-driven neck $nameOfConference


    • Fumagalli M, Gijsberts A, Ivaldi S et al. (2010), Learning to exploit proximal force sensing: A comparison approach $nameOfConference


    • Fumagalli M, Jamone L, Metta G et al. (2009), A force sensor for the control of a human-like tendon driven neck $nameOfConference


    • Nori F, Jamone L, Sandini G et al. (2007), Acc5urate control of a human-like tendon-driven neck $nameOfConference


    • Nori F, Metta G, Jamone L et al. (2006), Adaptive combination of motor primitives $nameOfConference

    • Jamone L, Metta G, Nori F et al. (2006), James: A humanoid robot acting over an unstructured world $nameOfConference


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