An Original Approach for a Better Remote Control of an Assistive Robot

Many researches have been done in the field of assistive robotics in the last few years. The first application field was helping with the disabled people\\u27s assistance. Different works have been performed on robotic arms in three kinds of situations. In the first case, static arm, the arm was principally dedicated to office tasks like telephone, fax... Several autonomous modes exist which need to know the precise position of objects. In the second configuration, the arm is mounted on a wheelchair. It follows the person who can employ it in more use cases. But if the person must stay in her/his bed, the arm is no more useful. In a third configuration, the arm is mounted on a separate platform. This configuration allows the largest number of use cases but also poses more difficulties for piloting the robot. The second application field of assistive robotics deals with the assistance at home of people losing their autonomy, for example a person with cognitive impairment. In this case, the assistance deals with two main points: security and cognitive stimulation. In order to ensure the safety of the person at home, different kinds of sensors can be used to detect alarming situations (falls, low cardiac pulse rate...). For assisting a distant operator in alarm detection, the idea is to give him the possibility to have complementary information from a mobile robot about the person\\u27s activity at home and to be in contact with the person. Cognitive stimulation is one of the therapeutic means used to maintain as long as possible the maximum of the cognitive capacities of the person. In this case, the robot can be used to bring to the person cognitive stimulation exercises and stimulate the person to perform them. To perform these tasks, it is very difficult to have a totally autonomous robot. In the case of disabled people assistance, it is even not the will of the persons who want to act by themselves. The idea is to develop a semi-autonomous robot that a remote operator can manually pilot with some driving assistances. This is a realistic and somehow desired solution. To achieve that, several scientific problems have to be studied. The first one is human-machine-cooperation. How a remote human operator can control a robot to perform a desired task? One of the key points is to permit the user to understand clearly the way the robot works. Our original approach is to analyse this understanding through appropriation concept introduced by Piaget in 1936. As the robot must have capacities of perceptio

Experiments in object tracking in image sequences

This thesis explores three object tracking algorithms for image sequences. These algorithms include the ensemble tracker, the EM-like mean-shift colour-histogram tracker, and the wandering-stable-lost scale-invariant feature transform (WSL-SIFT) tracker. The algorithms are radically different from one another. Despite their differences, they are evaluated on the same publicly available, moderately sized, research data sets which include 129 test cases in 13 different scenes. The results aid in fostering an understanding of their respective behaviours and in highlighting their flaws and failures. Lastly, an implementation setup is described that is suited to large-scale, grid computing, batch testing of these algorithms. Results clearly indicate that none of the evaluated trackers are suited to general purpose use. However, one may intelligently choose a tracker for a well-defined application by analysing the known scene characteristics

Pattern Recognition

A wealth of advanced pattern recognition algorithms are emerging from the interdiscipline between technologies of effective visual features and the human-brain cognition process. Effective visual features are made possible through the rapid developments in appropriate sensor equipments, novel filter designs, and viable information processing architectures. While the understanding of human-brain cognition process broadens the way in which the computer can perform pattern recognition tasks. The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms. The 27 chapters coved in this book disclose recent advances and new ideas in promoting the techniques, technology and applications of pattern recognition