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https://youtu.be/PmPUI-xX0CA
A grasping approach based on superquadric models
Published on May 22, 2017
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This video demonstrates grasping of objects using superquadric models. The method is described in the following paper:
Vezzani, G., Pattacini, U., and Natale, L., "A Grasping Approach Based on Superquadric Models", in IEEE International Conference on Robotics and Automation, Singapore, 2017
https://youtu.be/2Jmm4zel134
iCub - Behavior-based use of tool affordances for a table cleaning task
Published on Jun 5, 2017
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Tanis Mar, Vadim Tikhanoff, Lorenzo Natale
https://youtu.be/vHlPjv8tFUE
Visual end-effector tracking using a 3D model-aided particle filter for humanoid robot platforms
Published on Aug 3, 2017
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This video demonstrates recursive markerless estimation of a robot’s end-effector using visual observations from its cameras. The problem is formulated into the Bayesian framework and addressed using Sequential Monte Carlo (SMC) filtering. We demonstrate that the tracking is robust to clutter, allows compensating for errors in the robot kinematics and servoing the arm in closed loop using vision.
The method is described in the following paper:
C. Fantacci, U. Pattacini, V. Tikhanoff and L. Natale, "Visual end-effector tracking using a 3D model-aided particle filter for humanoid robot platforms", IEEE/RSJ International Conference on Intelligent Robots and Systems, Vancouver, BC, Canada, September 24-28, 2017.
https://youtu.be/2qcaLLipqPA
Markerless visual servoing on unknown objects for humanoid robot platforms
Published on Nov 10, 2017
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This video shows a new framework for markerless visual servoing on unknown objects in action. The pipeline consists of four main parts:
1) a least- squares minimization problem is formulated to find the volume of the object graspable by the robot’s hand using its stereo vision;
2) a recursive Bayesian filtering technique, based on Sequential Monte Carlo (SMC) filtering, estimates the 6D pose (position and orientation) of the robot’s end-effector without the use of markers;
3) a nonlinear constrained optimization problem is formulated to compute the desired graspable pose about the object;
4) an image-based visual servo control commands the robot’s end-effector toward the desired pose.
The method is described in the following preprint arXiv paper:
C. Fantacci, G. Vezzani, U. Pattacini, V. Tikhanoff and L. Natale, "Markerless visual servoing on unknown objects for humanoid robot platforms", arXiv preprint arXiv:1710.04465, 2017.
https://youtu.be/33F2G5mYiHY
iCub dynamic balancing and walking
Published on Mar 30, 2018
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This video shows the latest results in iCub whole-body control achieved by the Dynamic Interaction Control lab at the Italian Institute of Technology. In particular, the iCub balancing capabilities have been improved considerably, and the reactive quadratic-programming based controller ensures balance and safe interaction. Also, iCub walking capabilities have been implemented by means of on-line reactive model-predictive-control algorithms.
https://youtu.be/jemGKRxdAM8
iCub teleoperated walking and manipulation
Published on Sep 12, 2018
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Cite this contribution
- Teleoperation:
"Telexistence and Teleoperation for Walking Humanoid Robots"
submitted to IEEE Humanoids 2018
- Walking:
"A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots"
submitted to IEEE Humanoids 2018
This video shows the latest results achieved by the Dynamic Interaction Control Lab at the Italian Institute of Technology on teleoperated walking and manipulation for humanoid robots.
We have integrated the iCub walking algorithms with a new teleoperation system, thus allowing a human being to teleoperate the robot during locomotion and manipulation tasks.
https://youtu.be/vP70QCZhi8w
Dynamic Interaction Control lab's 2018 year in review
Published on Jan 2, 2019
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This video reviews the research results of the Dynamic Interaction Control lab obtained in 2018.
https://youtu.be/KTpRiPFbmuE
Will this ability put robots everywhere?
Published on Sep 3, 2019
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Meet the remarkable iCub that learns like a child, and can share its expertise with others.
Revolutions: The Ideas that Changed the World is the extraordinary story of six remarkable inventions: The Aeroplane, The Car, The Rocket, The Smartphone, The Telescope, The Robot. They are familiar, yet hidden within them are thousands of years of thought, struggle, sacrifice, determination and insight.
Each episode explores little-known stories and is packed with incredible ideas. The result is a mind-blowing science-led journey through human history, full of unintended consequences and incredible connections. It reveals how science, invention and technology build on one another to change everything. Mostly, it celebrates the achievements of the some of the greatest minds in human history.
Revolutions: The Ideas that Changed the World | Episode 6 Robots | BBC
https://youtu.be/Fb_R6IDDU4A
iCub reactive walking
Oct 9, 2020
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This video shows the latest results in the whole-body locomotion control of the humanoid robot iCub achieved by the Dynamic Interaction Control line (https://dic.iit.it/). In particular, the iCub now keeps the balance while walking and receiving pushes from an external user. The implemented control algorithms also ensure the robot to remain compliant during locomotion and human-robot interaction, a fundamental property to lower the possibility to harm humans that share the robot surrounding environment. The algorithms have been published in the proceedings of the 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids) ieeexplore.ieee.org/document/9034996 and the video shows their validation on the humanoid robot iCub.
https://youtu.be/t_bVOQnorPs
IFRR Robotics Global Colloquium "10 years with iCub"
May 6, 2021
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iCub is a humanoid robot designed to support research in embodied AI. At 104 cm tall, iCub has the size of a five year old child. It can crawl on all fours, walk, and sit up to manipulate objects. Its hands have been designed to support sophisticated manipulation skills. iCub is distributed as Open Source following the GPL licenses and can now count on a worldwide community of enthusiastic developers. The entire design is available for download from the project’s repositories (http://www.iCub.org). More than 40 robots have been built so far which are available in laboratories across Europe, US, Korea, Singapore, and Japan. It is one of the few platforms in the world with a sensitive full-body skin to deal with the physical interaction with the environment including possibly people. I will present the iCub project in its entirety showing how it is evolving towards fulfilling the dream of a personal humanoid in every home. Approach (optional): The iCub stance on artificial intelligence postulates that manipulation plays a fundamental role in the development of cognitive capability. As many of these basic skills are not ready- made at birth, but developed during ontogenesis, we aimed at testing and developing this paradigm through the creation of a child-like humanoid robot: i.e. the iCub. This “baby” robot is meant to act in daily life scenarios, performing tasks useful for learning while interacting with objects and people. The small (104cm tall), compact size (approximately 29kg and fitting within the volume of a child) and high number (53) of degrees of freedom combined with the Open-Source approach distinguish iCub from other humanoid robotics projects developed worldwide.