

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


Frontiers in Robotics & AI
I am glad to announce that our paper "Let's Push Things Forward: A Survey on Robot Pushing" has been accepted for publication by Frontiers in Robotics & AI journal. Follow the link below for the paper abstract https://www.frontiersin.org/articles/10.3389/frobt.2020.00008/abstract #frontiers #robot #pushing #survey #deeplearning #analytical #datadriven #frontiers #pushing #robot #survey #deeplearning #analytical #datadriven

Multisensory Learning Framework for Robot Drumming
The hype about sensorimotor learning is currently reaching high fever, thanks to the latest advancement in deep learning. In this paper, we present an open-source framework for collecting large-scale, time-synchronised synthetic data from highly disparate sensory modalities, such as audio, video, and proprioception, for learning robot manipulation tasks. We demonstrate the learning of non-linear sensorimotor mappings for a humanoid drumming robot that generates novel motion s

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