Obstacle Avoidance Procedure and Lee Algorithm Based Path Replanner for Autonomous Mobile Platforms

The paper proposes solution for two important issues connected to navigation of independent mobile platforms in an unknown environment. First issue relates to obstacle map, estimated based on stereovision images. It provides a basis for further platform path-planning. The main problem that has to be solved in obstacle map derivation is elimination of artifacts resulting from depth estimation. Thus a two-step artifact filtering procedure is proposed, which exploits both within-frame spatial correlations as well as temporal, between-frame correlations to do this task. Second procedure, based on well-known Lees algorithm is designed for obtaining vehicle collisionless path. Such routes need to be updated on-the-fly to take into account moving obstacles or newly detected objects. The main idea of the proposed approach is to identify regions where environment has changed and to execute a procedure of selective path updates. As a result, an optimal path can be derived at a computational expense comparable to the heuristic Lifelong A* search. Experiment results demonstrate efficiency of the two discussed approaches for platform operation control in real environments, where both static and moving obstacles are present

Vergence and Gaze Based 3D Mapping of Local Environment

This disclosure describes techniques for utilizing a user’s natural perception of their environment to obtain information about the local environment. With user permission, eye positions and eye movements of a user as they interact with their environment are utilized to substitute for and/or augment machine-based perception of the environment. Eye movement information such as vergence, fixation/gaze points, saccade patterns, etc. are obtained from eye tracking sensors. A 3D volumetric map of the environment is created based on the eye movement information. Based on identified user fixations, an interest map of the room is generated. 3D spatial information can be obtained in user environments where an outward facing camera is infeasible, since mapping can be performed based only on vergence information obtained from the eyes

A 3D Omnidirectional Sensor For Mobile Robot Applications

International audienc

Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System

Az http://intechweb.org/ alatti "Books" fül alatt kell rákeresni a "Stereo Vision" címre és az 1. fejezetre

Under vehicle perception for high level safety measures using a catadioptric camera system

In recent years, under vehicle surveillance and the classification of the vehicles become an indispensable task that must be achieved for security measures in certain areas such as shopping centers, government buildings, army camps etc. The main challenge to achieve this task is to monitor the under frames of the means of transportations. In this paper, we present a novel solution to achieve this aim. Our solution consists of three main parts: monitoring, detection and classification. In the first part we design a new catadioptric camera system in which the perspective camera points downwards to the catadioptric mirror mounted to the body of a mobile robot. Thanks to the catadioptric mirror the scenes against the camera optical axis direction can be viewed. In the second part we use speeded up robust features (SURF) in an object recognition algorithm. Fast appearance based mapping algorithm (FAB-MAP) is exploited for the classification of the means of transportations in the third part. Proposed technique is implemented in a laboratory environment

TRAJECTOGRAPHY ESTIMATION FOR A SMART POWERED WHEELCHAIR ORB-SLAM2 VS RTAB-MAP A PREPRINT

International audienceThis work is part of the ADAPT project relating to the implementation of a trajectography functionality that aims to measure the path travelled by a patient during the clinical trials. This system (hardware and software) must be reliable, quickly integrable, low-cost and real-time. Therefore, our choices have been naturally made towards visual SLAM-based solutions coupled with an Intel real-sense consumer sensors. This paper is a comparison of two well-known visual SLAM algorithms in the scientific community, ORB-SLAM2 and RTAB-Map, evaluated in different path configurations. The added value of our work lies in the accurate estimation of the trajectories achieved through the use of a VICON motion capture system

Istraživanje simultane lokalizacije, kalibracije i kartiranja umreženim robotskim sustavima

In a network robot system, a robot and a sensor network are integrated smoothly to develop their advantages and benefit from each other. Robot localization, sensor network calibration and environment mapping are three coupled issues to be solved once network robot system is introduced into a service environment. In this article, the problem of simultaneous localization, calibration and mapping is raised in order to improve their precision. The coupled relations among localization, calibration and mapping are denoted as a joint conditional distribution and then decomposed into three separate analytic terms according to Bayesian and Markov properties. The framework of Rao-Blackwellized particle filtering is used to solve the three analytic terms, in which extended particle filter is used for localization and unscented Kalman filter is used for both calibration and mapping. Simulations have been performed to demonstrate the validity and efficiency of the proposed solutions.U umreženom robotskom sustavu, robot i senzorska mreža su međusobno integrirani i povezani na način da i jedan i drugi iskoriste svoje prednosti, te da imaju koristi jedan od drugoga. Kako bi umreženi robotski sustav mogao djelovati u radnom okruženju potrebno je riješiti tri međusobno povezana problema: lokalizaciju, kalibraciju senzorske mreže i kartiranje prostora. U ovom radu razmatraju se problemi istodobne lokalizacije, kalibracije i kartiranja te se razmatraju mogućnosti poboljšanja njihove preciznosti. Povezanost lokalizacije, kartiranja i kalibracije predstavljena je pomoću zajedničke uvjetne razdiobe i zatim rastavljena u tri razdvojena analitička izraza korištenjem Bayesovih i Markovljevih svojstava. Za rješavanje svih triju analitičkih izraza koristi se Rao-Blackwell čestično filtriranje, pri čemu se prošireni čestični filtar koristi kod lokalizacije a nederivirajući Kalmanov filtar za kalibraciju i kartiranje. Ispravnost i efikasnost predloženog pristupa pokazana je kroz provedene simulacije

Inter-Row Tree Detection and Tracking Schemes For Structural Plantation Area

In this work, an inter-row tree detection and tracking techniques based on Simultaneous Localization and Mapping (SLAM) method is developed specifically for a well-structures agricultural field where the trees are planted uniformly with certain distance that leaves it with a number of inter-row spaces. The existing rows has created opportunities for an autonomous vehicle to navigate in between the trees to perform the plantation activities such as scouting, monitoring, rowing, pesticide spraying and others. A new approach to detect the landmarks and navigate in the farm based on the lightweight sensors and less computation effort is proposed. In this method, the tree detection and diameter estimation techniques implement the modified tree-triangle diameter technique by using innovative technique based on infrared sensors. Then, in substituting the GPS signal problems during the navigation and localization problems, a curve-based navigation approach is formulated. The path is planned based on the third-polynomial Bezier curve by projecting series of waypoints to create a solid path from one point to another. Then, the trajectory plan is derived for the autonomous vehicle to follow these waypoints during the navigation. At the same time, the mapping technique implements the memory utilization method in order to ease the localization process as well as landmarks mapping in the visual map which is oriented in two-dimensional coordinate format. All of these functions are created, formulated and tested thoroughly in the embedded microcontroller development board platform by using dsPIC30F6014A chip on the omnidirectional vehicle platform