HANDLE: Developmental Pathway Towards Autonomy and Dexterity in Robot In-Hand Manipulation is an European project coordinated by the university Pierre and Marie Curie of Paris and include a consortium formed by nine partners from six EU countries: France, UK, Spain, Portugal, Sweden and Germany.
The field of robotics is undergoing a major revolution as it is increasingly
being applied to general purposes outside the production line: for health,
rehabilitation and professional services, in domestic and leisure
environments, as well as hazardous environments. There, one keystone for
robots to carry out accurate and intelligent tasks, with and for people, is
their ability both to handle autonomously all sorts of objects and to use
human tools. However, today's robots are unable to achieve dexterous and
fine manipulation, especially when this requires in-hand manipulation. They
are far from being able to understand and reason about their environments,
their goals and their own capabilities, to learn skills and improve their
performance by what they have been taught and their own experience, to
interact with their environments with the efficiency of humans.
The HANDLE project aims at understanding how humans perform the manipulation of objects in order to replicate grasping and skilled in-hand movements with an anthropomorphic artificial hand, and thereby move robot grippers from current best practice towards more autonomous, natural and effective articulated hands. The project implies not only focusing on technological developments but also working with fundamental multidisciplinary research aspects in order to endow the robotic hand system with advanced perception capabilities, high level feedback control and elements of intelligence that allow recognition of objects and context, reasoning about actions and a high degree of recovery from failure during the execution of dexterous tasks.
Integrating findings from disciplines such as neuroscience, developmental psychology, cognitive science, robotics, multimodal perception and machine learning, the method we will develop is based on an original blend of learning and predicting behaviours from imitation and "babbling" to allow the robot to be capable of responding to gaps in its knowledge.
The project involves a team of researchers from IDMEC/IST, from ISR/Coimbra from the University of Minho.
The global goal of the project is the design of a solution based on a
small size airship as an aerial stable platform for a semi-autonomous
monitoring and surveillance mission.
This is a project in the area of aerial robotics, an area which has justified a growing interest in recent times, with very different application objectives, namely in the civilian domain, for monitoring of roads, detection of forest fires, inspection of power lines. Among the advantages of the airship solution, we may cite its natural stability, low operational costs, reduced pollution, and the ability to move at very low airspeeds or even hover.
The long period of absence of airships resulted in a lower knowledge of their potential usage and flight characteristics. A first objective of the project is to permit a better description of its flight characteristics and propose alternative solutions based on the most recent control techniques, resulting in an aerial platform for semi-autonomous monitoring, with adequate mobility and stability characteristics. The project involves both the area of aerodynamics and the area of modelling and control, along with the area of systems integration, including the relevant aspects of mission safety.
A second objective, already mentioned as an application mission, is to explore the mobility of the airship to develop a surveillance system based on images, to monitor and recognize the motion of objects, allowing the inspection of ground areas with the reference of digital maps drawn from the airship cameras, from a low/medium altitude.
The following list is a set of architecture specifications and concepts, separated in airship and ground control categories:
The Bayesian approach will be used to develop artificial cognitive systems concerned with:
BACS - Bayesian Approach to Cognitive Systems is an Integrated Project conducted under the Thematic Priority: Information Society Technologies - Sub-topic: Cognitive Systems - of the 6th Framework Program of the European Commission.
Main Goal and Objectives
By taking up inspiration from the brains of mammals, including humans, the BACS project will investigate and apply Bayesian models and approaches in order to develop artificial cognitive systems that can carry out complex tasks in real-world environments.