Laser Reflection Intensity and Multi-Layered Laser Range Finders for People Detection

Abstract-Successful detection of people is a basic requirement for a robot to achieve symbiosis in people's daily life. Specifically, a mobile robot designed to follow people needs to keep track of people's position through time, for it defines the robot's position and trajectory. In this work we introduce the usage of reflection intensity data of Laser Range Finders (LRF) arranged in multiple layers for people detection. We use supervised learning to train strong classifiers including intensity-based features. Concretely, we propose a calibration method for laser intensity and introduce new intensity-based features for people detection which are combined with range-based features in a strong classifier using supervised learning. We provide experimental results to evaluate the effectiveness of these features. This work is an step towards of our main research project of developing a social autonomous mobile robot acting as member of a people group

Detection of Road Surface Damage Using Mobile Robot Equipped with 2D Laser Scanner

Abstract-This paper introduces a road surface damage detection using mobile robot. Our research is aimed autonomous sidewalk investigation with mobile robot, for reduce the burden of human workers engaged in road maintenance. A mobile robot moves along the route for investigation and obtain shape information of road surface using 2D laser scanner. From this road surface information, road damage section will be automatically detected. By showing the detection result instead of site investigation by human workers, it expects to reduce the burden of human workers. Road surface have gradual curves and some road damage is small and less than 2 cm. Hence, our method uses random sampling to detect irregularity as road damage. This paper explains the measurement of road surface using mobile robot equipped with 2D laser scanner and the road damage detection method. In this paper, some experimental results also is shown

Development of ultra-small lightweight optical range sensor system

Abstract -We have developed a 2-D laser range sensor suitable for mobile robot platforms. The sensor features compactness, lightweight, high precision and low power consumption, and provides the wide scan angle with high resolution, which is very important for environment recognition by mobile robots. The basic technology for measuring the distance between the sensor and objects are; using amplitude modulation of light waves and detecting the phase difference between transmitted and the received one. This paper explains the specification of the proto-type sensor, the method of distance measurement and examples of experimental results

Autonomous Indoor Mobile Robot Navigation by Detecting Fluorescent Tubes

This paper proposes an indoor navigation system for an autonomous mobile robot including the teaching of its environment. The self-localization of the vehicle is done by detecting the position and orientation of fluorescent tubes located above it’s desired path thanks to a camera pointing to the ceiling. A map of the lights based on odometry data is built in advance by the robot guided by an operator. Then a graphic user interface is used to define the trajectory the robot must follow with respect to the lights. While the robot is moving, the position and orientation of the lights it detects are compared to the map values, which enables the vehicle to cancel odometry errors.

A People-Localization Method for Multi-Robot Systems First Approach for Guiding-Tours

Throughout this article we present a methodology to localize multiple people in a group by a multi-robot system (MRS). The aim of the MRS is to conduct people through hallways in indoors as a guided-tour service task. However, further than guidance process, we detail a method for humans' localization by sharing distributed sensor data arising from the team of robots instrumented with stereo vision. The robustness of the method is presented, and by matching the real environment against the computed results, error in human localization is showed as well. As a first approach of the entire MRS goal, this paper explains from a task approach the way for environment ranging, spatial noise filtering, distributed sensor data fusion and clustering based segmentation. Likewise, through the paper experimental results are shown to verify the feasibility of the method