A Comparison of SLAM Algorithms with Range Only Sensors

2014 IEEE International Conference on Robotics and Automation (ICRA),31 May 2014 - 07 June 2014, Hong-Kong, ChinaLocalization and mapping in indoor environments, such as airports and hospitals, are key tasks for almost every robotic platform. Some researchers suggest the use of RO (Range Only) sensors based on WiFi (Wireless Fidelity) technology with SLAM (Simultaneous Localization And Mapping) techniques. The current state of the art in RO SLAM is mainly focused on the filtering approach, while the study of smoothing approach with RO sensors is quite incomplete. This paper presents a comparison between a filtering algorithm, the EKF, and a smoothing algorithm, the SAM (Smoothing And Mapping). Experimental results are obtained, first in an outdoor environment using two types of RO sensors and then in an indoor environment with WiFi sensors. The results demonstrate the feasibility of the smoothing approach with WiFi sensors in indoors

Human activity recognition applying computational intelligence techniques for fusing information related to WiFi positioning and body posture

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE WCCI 2010, 18/07/2010-23/07/2010, Barcelona, España.This work presents a general framework for people indoor activity recognition. Firstly, a Wireless Fidelity (WiFi) localization system implemented as a Fuzzy Rulebased Classifier (FRBC) is used to obtain an approximate position at the level of discrete zones (office, corridor, meeting room, etc). Secondly, a Fuzzy Finite State Machine (FFSM) is used for human body posture recognition (seated, standing upright or walking). Finally, another FFSM combines bothWiFi localization and posture recognition to obtain a robust, reliable, and easily understandable activity recognition system (working in the desk room, crossing the corridor, having a meeting, etc). Each user carries with a personal digital agenda (PDA) or smart-phone equipped with a WiFi interface for localization task and accelerometers for posture recognition. Our approach does not require adding new hardware to the experimental environment. It relies on the WiFi access points (APs) widely available in most public and private buildings. We include a practical experimentation where good results were achieved.Ministerio de Ciencia e InnovaciónComunidad de Madri

Automatic traffic signs and panels inspection system using computer vision

Computer vision techniques applied to systems used on road maintenance, which are related either to traffic signs or to the road itself, are playing a major role in many countries because of the higher investment on public works of this kind. These systems are able to collect a wide range of information automatically and quickly, with the aim of improving road safety. In this context, the correct visibility of traffic signs and panels is vital for the safety of drivers. This paper describes an approach to the VISUAL Inspection of Signs and panEls (“VISUALISE”), which is an automatic inspection system, mounted onboard a vehicle, which performs inspection tasks at conventional driving speeds. VISUALISE allows for an improvement in the awareness of the road signaling state, supporting planning and decision making on the administration's and infrastructure operators' side. A description of the main computer vision techniques and some experimental results obtained from thousands of kilometers are presented. Finally, the conclusions of the system are described