A multifingered robotic hand and an object that will be grasped and manipulated by the hand are the components of a dexterous manipulation robotic system. Then, the dexterous manipulation problem can be defined as the act of determining how to alter a grasp of an object through the coordinated motion of the fingers to reach a desired change in its position and orientation.
In structured environments, that is, in worlds whose characteristics are well known in advance, solving the dexterous manipulation problem reduces to optimising hardware and software for dealing with the specific objects and constraints present in the sought task. Since in these cases all possible ramifications are documented, the design optimisation usually concludes that multi-degree-of-freedom robot arms with simple two-finger jaw or vacuum grippers are enough to position and orient the manipulated objects; thus avoiding the difficulties associated with implementing robot hand dexterity.
In other words, as a result of the described analysis, fine manipulation, which refers to the manipulation of objects by small robot parts such as robotic fingers, hands, and wrists, is absorbed by gross manipulation, which refers to the manipulation of objects by large robot parts such as robotic arms or other types of limbs. This is certainly the typical situation observed in many of the current industrial applications, as demonstrated by the design of the most recent collaborative industrial robots.
The above reasoning gives a simple explanation about the lack of use of multifingered dexterous robotic hands in industrial settings, an aspect that have been the subject of discussion in the robotic manipulation community recently, and clearly opens the question about why this technology and research on the dexterous manipulation problem is a pressing need.
The answer of such a query is simple: the solution of some of the most relevant social, environmental, and economic challenges of this century, and beyond, (e.g., an efficient healthcare, coping with an ageing population, management of mega cities), requires robots that cooperate with humans to manipulate objects designed for human hands. Thus, given the diversity and uncertainty inherent of such settings, robot manipulation technologies require the cooperation, not the absorption, of gross manipulation and fine manipulation. Solving the problem of manipulating objects dexterously in unstructured environments is then a must.
However, despite the substantial progress made in the last 35-40 years in robotics, performing reliable dexterous manipulation operations under both shape diversity and shape uncertainty with a robot hand is still an open question. The aim of this research is to help solving this problem and shaping the next generation of robot hand technologies by investigating novel morphologies and low-level control schemes that drastically enhance the dexterous manipulation capabilities of current solutions.
Specifically, this research focuses on devising robot hands based on flexible and adaptive mechanical components that generate non-trivial predictable behaviours of the hand-object system that are able to be controlled in open loop, that is, without feedback control and without knowing the particularities of the object beforehand, while still being robust to the size or shape of the object being manipulated. This novel approach, called 'trustable dexterous manipulation', departs from traditional hand-centred strategies to embrace a holistic view that takes into account the manipulated bodies without losing generality; it has the potential to redefine the current practice in design of dexterous robot hands.
The success of this project will benefit researchers and practitioners working on technologies that involve robots collaborating with humans in dynamic and uncertain settings across multiple domains, including agriculture, healthcare, manufacturing, and extreme environments.
|