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Minimally invasive surgery (MIS) has been the preferred surgery approach owing to its advantages over conventional open surgery. As a major limitation, the lack of tactile perception impairs the ability of surgeons in tissue distinction and maneuvers. Many studies have been reported on industrial robots to perceive various tactile information. However, only force data are widely used to restore part of the surgeon’s sense of touch in MIS. In recent years, inspired by image classification technologies in computer vision, tactile data are represented as images, where a tactile element is treated as an image pixel. Processing raw data or features extracted from tactile images with artificial intelligence (AI) methods, including clustering, support vector machine (SVM), and deep learning, has been proven as effective methods in industrial robotic tactile perception tasks. This holds great promise for utilizing more tactile information in MIS. This review aims to provide potential tactile perception methods for MIS by reviewing literatures on tactile sensing in MIS and literatures on industrial robotic tactile perception technologies, especially AI methods on tactile images.

Minimally invasive surgery (MIS) has been the preferred surgery approach owing to its advantages over conventional open surgery. As a major limitation, the lack of tactile perception impairs the ability of surgeons in tissue distinction and maneuvers. Many studies have been reported on industrial robots to perceive various tactile information. However, only force data are widely used to restore part of the surgeon's sense of touch in MIS. In recent years, inspired by image classification technologies in computer vision, tactile data are represented as images, where a tactile element is treated as an image pixel. Processing raw data or features extracted from tactile images with artificial intelligence (AI) methods, including clustering, support vector machine (SVM), and deep learning, has been proven as effective methods in industrial robotic tactile perception tasks. This holds great promise for utilizing more tactile information in MIS. This review aims to provide potential tactile perception methods for MIS by reviewing literatures on tactile sensing in MIS and literatures on industrial robotic tactile perception technologies, especially AI methods on tactile images. [ABSTRACT FROM AUTHOR]

This paper discusses rock art in southern Scandinavia as a multisensory format, where both sight and touch would have contributed to the comprehension of the images. From a structural semiotic point of view, we suggest that rock art can be construed as an organised set of features, such as visual and tactile elements, organised into heterogeneous unities with dynamic relations between elements that can change over time with respect to how they are experienced. We argue that in order to understand the rock art medium, it is crucial to take into consideration the multisensory interaction between the perceiver and the qualities of the rock art surface. The reason for including tactile elements in our interpretation of the conception of rock art is the way it was created: by hands interacting with tools and rock surfaces, as well as the spontaneous human tendency to explore the physical world through touch. One can identify key features in the images that would arguably facilitate tactile recognition, as well as be better explained from a multisensorial perspective. This includes the position of the images on horizontal outcrops, the moderate size of the images, the application of an orthographic perspective, the use of 'tactile markers' (ie crucial features having a strategic function for understanding images by touch), and the occurrence of incomplete images. A multisensorial perspective on rock art furthermore has semiotic implications. Incomplete images, for example, can be understood as indexical stand-ins for the whole imagined picture, ie as iconic indices. A multisensorial approach to Scandinavian rock art thus allows for new explanations for certain design choices, as well as a new understanding of how the images could relay meaning to a perceiver. [ABSTRACT FROM AUTHOR]

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments.

The field of in-hand robot manipulation of deformable objects is an open and key issue for the next-coming robots. Developing an adaptable and agile framework for the tasks where a robot grasps and manipulates different kinds of deformable objects, is a main goal in the literature. Many research works have been proposed to control the manipulation tasks using a model of the manipulated object. Despite these techniques are precise to model the deformations, they are time consuming and, using them in real environments is almost impossible because of the large amount of objects which the robot could find. In this paper, we propose a model-independent framework to control the movements of the fingers of the hands while the robot executes manipulation tasks with deformable objects. This technique is based on tactile images which are obtained as a common interface for different tactile sensors, and uses a servo-tactile control to stabilize the grasping points, avoid sliding and adapt the contacts’ configuration regarding to position and magnitude of the applied force. Tactile images are obtained using a combination of dynamic Gaussians, which allows the creation of a common representation for tactile data given by different sensors with different technologies and resolutions. The framework was tested on different manipulation tasks where the objects are deformed, and without using a model of them. [ABSTRACT FROM AUTHOR]

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF) is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments. [ABSTRACT FROM AUTHOR]

Abstract: People with a sight problem can face many barriers when visiting museums and galleries. Talking Images is a user-led research project that has aimed to explore these barriers and offer solutions to improve access at museums, galleries and heritage sites for blind and partially sighted people. The project has been a collaboration between RNIB and Vocaleyes and has involved blind and partially sighted people in extensive consultation and research. A team of 12 blind and partially sighted auditors visited a wide range of venues across the UK. The auditors compiled over 60 detailed reports on audio guides and other services used at these venues, along with comments on the welcome and customer service they received. The venues that participated in the project also completed questionnaires on the services they provide, along with information on policy, training and marketing. In addition, 270 blind and partially sighted people took part in a phone survey, which examined people''s experiences at museums, galleries and heritage attractions. Drawing on the findings of this research, Vocaleyes undertook case studies in partnership with three venues to develop new audio tours. Each project was overseen by consultative groups of blind and partially sighted people who advised the development of the projects from the initial stages through to evaluation. The poster presentation will outline the scope of the project and partnerships, the various research studies, their aims and findings, and quotes from the auditors and focus group members on their experiences at museums, galleries and heritage sites across the UK. Prior knowledge of the topic is not assumed. The paper does not contain advanced technical content. [Copyright &y& Elsevier]

Members of the blind and visually impaired community rely heavily on tactile illustrations - raised line graphics on paper that are felt by hand - to understand geometric ideas in school textbooks, depict a story in children's books, or conceptualize exhibits in museums. However, these illustrations often fail to achieve their goals, in large part due to the lack of understanding in how 3D shapes can be represented in 2D projections. This paper describes a new technique to design tactile illustrations considering the needs of blind individuals. Successful illustration design of 3D objects presupposes identification and combination of important information in topology and geometry. We propose a twofold approach to improve shape understanding. First, we introduce a part-based multi-projection rendering strategy to display geometric information of 3D shapes, making use of canonical viewpoints and removing reliance on traditional perspective projections. Second, curvature information is extracted from cross sections and embedded as textures in our illustrations. [ABSTRACT FROM AUTHOR]

Blind students are bound to make up a very small part of the population most university lecturers will encounter during their careers. Research to date shows that good communication between staff and student improves the chances of a successful outcome for both parties. The research does show, however, that the exercise seems to be one of re-inventing the wheel, perhaps with a less than fully informed blueprint to work from. The authors use their own experiences as blind students who progressed beyond research methods or first year introductory courses into careers as teachers and researchers of statistical methods to provide guidance for their sighted colleagues. Our principle point of difference to the existing research work is that we rely on the experience of our statistical education for our current livelihoods; we were not one-off students taking a research methodology course or first year introductory course. We benefitted from the successful (and possibly the not so successful) interactions we had with our sighted teachers. It is our hope that by saving staff from wasted effort, we can spare students from unnecessary discomfort in classes that could improve their future employment prospects. Our aim is therefore to provide practical support for our sighted colleagues and blind peers as we work together towards the empowerment of blind students in becoming competent producers of statistical information, not just consumers who interpret that information. [ABSTRACT FROM AUTHOR]