TII's Robotics Research for Tomorrow's Technology (R2T2) 2021
I'm SUPER excited to announce the opening of the Call for Abstract for TII's Robotics Research for Tomorrow's Technology (R2T2) seminar 2021. Read more... #robotics #research #TII #ARRC #seminar2021 #R2T2
Efficient Human-like Dexterous Grasping under Uncertainty for Robotics
Imagine that you are reaching into the fridge to grasp an object you can only partially see. Rather than relying solely on vision, you must use touch in order to localise it and securely grasp it. However, humans would not poke the object to localise it first and then grasp it. We compensate for the uncertainty by approaching the object in a way such that if a contact occurs it will generate enough information about where the object is and the object will be grasped with a mi
Joint Robot-Human Logistics and Assembly in Aerospace
Link to video: https://www.youtube.com/watch?time_continue=3&v=5Fuhk4oKIvY Human robot collaboration on the shop floor presents a significant set of challenges. In this project we have developed methods for enabling a shop floor mobile robot to assist a human in logistical and assembly tasks, by bringing tools, parts and assisting in the assembly process to reduce the strain on the human worker. The scenario is as follows. In structure assembly, equipment installation and fin
Cybernetic Skivvies (The Economist)
'Cleaning up nuclear wast is obviously a task for robots. But designing 'bots that can do that is hard'. This is how the latest article on the National Centre for Nuclear Robotics (NCNR) starts. A good read from The Economist. Link to the article: https://www.economist.com/science-and-technology/2019/06/20/cleaning-up-nuclear-waste-is-an-obvious-task-for-robots #ExtremeRoboticsLab #Robotics #NationalCentreforNuclearRobotics #NCNR #ERL #CybernaticSkivvies #Economist #ScienceTe
'Feature-Based Transfer Learning for Robotic Push Manipulation'
Our paper entitled 'Feature-Based Transfer Learning for Robotic Push Manipulation' published in 2018 IEEE International Conference on Robotics and Automation (ICRA) has been selected for an extended version by the Special Issue on Advancement in Engineering and Computer Science organized by Advances in Science, Technology and Engineering Systems Journal (ASTESJ) Thanks to my students, Rhys Howard and Jochen Stuber, the extended paper also proposed a improvement of a twofold i
Selected finalist for the Best Student Paper award at ICORR 2019
The 16th IEEE/RAS-EMBS International Conference on Rehabilitation Robotics (ICORR 2019) [Toronto, Canada, June 24–28] is a bi-annual appointment on theoretical and experimental issues in the fields of Rehabilitation Robotics and Neuroscience applied to Healthcare. Prosthetic, assistive, diagnostic, and therapeutic robots continue to face challenges of adoption by the users. Karoline Heiwolt, a CNCR student, has developed under my supervision a novel approach to make myocontro
Towards Robots that We can Trust
As robots make their way into our homes, the ability to predict how their actions affect the environment is a key skill that they need to possess to operate in safety and gain our trust. In this work, we review the robotic pushing literature. While focusing on work concerned with predicting the motion of pushed objects, we also cover relevant applications of pushing for planning and control. This paper is concerned with the evolution of forwards models (FMs) and their applica
Birmingham researchers use artificial intelligence to advance the dexterity of robots
Link to the article about our GPAtlasRRT algorithm for tactile recovering of the shape of novel objects. https://www.birmingham.ac.uk/university/colleges/eps/news/2018/7/birmingham-researchers-artificial-intelligence-advance-dexterity-robots.aspx #rrt #gp #atlas #robotics #robot #tactile #exploration #touch #novelobjects #vito #boris #softhand #humanoid #ai #artificialintelligence #dexterity #universityofbirmingham #irlab #uob #pisa
2D Linear Time-Variant Controller for Human's Intention Detection for Reach-to-Grasp Trajectorie
Designing robotic assistance devices for manipulation tasks is challenging. This work is concerned with improving accuracy and usability of semi-autonomous robots, such as human operated manipulators or exoskeletons. The key insight is to develop a system that takes into account context- and user-awareness to take better decisions in how to assist the user. The context-awareness is implemented by enabling the system to automatically generate a set of candidate grasps and reac
Feature-Based Transfer Learning for Robotic Push Manipulation
This work presents a data-efficient approach to learning transferable forward models for robotic push manipulation. Our approach extends previous work on modular contact-based predictors by leveraging information on the pushed object's local surface features. We test the hypothesis that, by conditioning predictions on local surface features, we can achieve generalisation across objects of different shapes. Our approach involves learning motion models that are specific to con
