Cognitive robotics: a new approach to simultaneous localisation and mapping

Most simultaneous localisation and mapping (SLAM) solutions were developed for navigation of non-cognitive robots. By using a variety of sensors, the distances to walls and other objects are determined, which are then used to generate a map of the environment and to update the robot’s position. When developing a cognitive robot, such a solution is not appropriate since it requires accurate sensors and precise odometry, also lacking fundamental features of cognition such as time and memory. In this paper we present a SLAM solution in which such features are taken into account and integrated. Moreover, this method does not require precise odometry nor accurate ranging sensors.

Diversidade de macrofungos em sobreiral serrano do sul de Portugal: sua relação com a gestão florestal

Dissertação de mest., Gestão e Conservação da Natureza, Faculdade de Ciências do Mar e do Ambiente, Univ. do Algarve, 2007

Multi-scale cortical keypoints for realtime hand tracking and gesture recognition

Human-robot interaction is an interdisciplinary research area which aims at integrating human factors, cognitive psychology and robot technology. The ultimate goal is the development of social robots. These robots are expected to work in human environments, and to understand behavior of persons through gestures and body movements. In this paper we present a biological and realtime framework for detecting and tracking hands. This framework is based on keypoints extracted from cortical V1 end-stopped cells. Detected keypoints and the cells’ responses are used to classify the junction type. By combining annotated keypoints in a hierarchical, multi-scale tree structure, moving and deformable hands can be segregated, their movements can be obtained, and they can be tracked over time. By using hand templates with keypoints at only two scales, a hand’s gestures can be recognized.