Haptic Intelligence Talk Biography
09 June 2020 at 10:00 - 11:00 | remote talk on Zoom

Robotic Manipulation: a Focus on Object Handovers

Valerio photo2

Humans perform object manipulation in order to execute a specific task. Seldom is such action started with no goal in mind. In contrast, traditional robotic grasping (first stage for object manipulation) seems to focus purely on getting hold of the object—neglecting the goal of the manipulation. In this light, most metrics used in robotic grasping do not account for the final task in their judgement of quality and success. Since the overall goal of a manipulation task shapes the actions of humans and their grasps, the task itself should shape the metric of success. To this end, I will present a new metric centred on the task. The task is also very important in another action of object manipulation: the object handover. In the context of object handovers, humans display a high degree of flexibility and adaptation. These characteristics are key for robots to be able to interact with the same fluency and efficiency with humans. I will present my work on human-human and robot-human handovers and explain why an understanding of the task is of importance for robotic grasping.

Speaker Biography

Valerio Ortenzi ()

Dr Valerio Ortenzi qualified with a BSc in Automation and Control Engineering from Sapienza University of Rome in 2010. He went on to study for a MSc in Artificial Intelligence and Robotics Engineering, 2012, from Sapienza University of Rome, and then a PhD in Robotics in 2017, from the University of Birmingham, UK. He then joined the Centre of Excellence in Robotic Vision at Queensland University of Technology, Brisbane, as a Research Fellow with Dist. Prof. Peter Corke. He has returned to the University of Birmingham as a Research Fellow from October 2018 to April 2020. His research interests focus on human-robot interaction and robotic manipulation. New directions of his work go into neuroscience and psychology of human grasping together with robotic vision, to ameliorate the efficiency of human-robot handover of objects.