Viewfinder: final activity report

The VIEW-FINDER project (2006-2009) is an 'Advanced Robotics' project that seeks to apply a semi-autonomous robotic system to inspect ground safety in the event of a fire. Its primary aim is to gather data (visual and chemical) in order to assist rescue personnel. A base station combines the gathered information with information retrieved from off-site sources. The project addresses key issues related to map building and reconstruction, interfacing local command information with external sources, human-robot interfaces and semi-autonomous robot navigation. The VIEW-FINDER system is a semi-autonomous; the individual robot-sensors operate autonomously within the limits of the task assigned to them, that is, they will autonomously navigate through and inspect an area. Human operators monitor their operations and send high level task requests as well as low level commands through the interface to any nodes in the entire system. The human interface has to ensure the human supervisor and human interveners are provided a reduced but good and relevant overview of the ground and the robots and human rescue workers therein

Vehicle Trajectory from an Uncalibrated Stereo-Rig with Super-Homography

International audienceWe present in this article an original manner to estimate the trajectory of a vehicle running in urban-like areas. The method consists in extracting then tracking features (points, lines) with an uncalibrated stereo-rig from the road assumed as a plane to compute homographies relative to the camera(s) motions. The purposed method copes with the dense traffic conditions: the free space required (first ten meters in front of the vehicle) is slightly equivalent to the security distance between two vehicles. Experimental issues from real data are presented and discussed

Fade Depth Prediction Using Human Presence for Real Life WSN Deployment

Current problem in real life WSN deployment is determining fade depth in indoor propagation scenario for link power budget analysis using (fade margin parameter). Due to the fact that human presence impacts the performance of wireless networks, this paper proposes a statistical approach for shadow fading prediction using various real life parameters. Considered parameters within this paper include statistically mapped human presence and the number of people through time compared to the received signal strength. This paper proposes an empirical model fade depth prediction model derived from a comprehensive set of measured data in indoor propagation scenario. It is shown that the measured fade depth has high correlations with the number of people in non-line-of-sight condition, giving a solid foundation for the fade depth prediction model. In line-of-sight conditions this correlations is significantly lower. By using the proposed model in real life deployment scenarios of WSNs, the data loss and power consumption can be reduced by the means of intelligently planning and designing Wireless Sensor Network

Body-relative navigation guidance using uncalibrated cameras

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 89-97) and index.The ability to navigate through the world is an essential capability to humans. In a variety of situations, people do not have the time, the opportunity or the capability to learn the layout of the environment before visiting an area. Examples include soldiers in the field entering an unknown building, firefighters responding to an emergency, or a visually impaired person walking through the city. In absence of external source of localization (such as GPS), the system must rely on internal sensing to provide navigation guidance to the user. In order to address real-world situations, the method must provide spatially extended, temporally consistent navigation guidance, through cluttered and dynamic environments. While recent research has largely focused on metric methods based on calibrated cameras, the work presented in this thesis demonstrates a novel approach to navigation using uncalibrated cameras. During the first visit of the environment, the method builds a topological representation of the user's exploration path, which we refer to as the place graph. The method then provides navigation guidance from any place to any other in the explored environment. On one hand, a localization algorithm determines the location of the user in the graph. On the other hand, a rotation guidance algorithm provides a directional cue towards the next graph node in the user's body frame. Our method makes little assumption about the environment except that it contains descriptive visual features. It requires no intrinsic or extrinsic camera calibration, and relies instead on a method that learns the correlation between user rotation and feature correspondence across cameras. We validate our approach using several ground truth datasets. In addition, we show that our approach is capable of guiding a robot equipped with a local obstacle avoidance capability through real, cluttered environments. Finally, we validate our system with nine untrained users through several kilometers of indoor environments.by Olivier Koch.Ph.D

Plausibility Verification for 3D Object Detectors Using Energy-Based Optimization

Environmental perception obtained via object detectors have no predictable safety layer encoded into their model schema, which creates the question of trustworthiness about the system\u27s prediction. As can be seen from recent adversarial attacks, most of the current object detection networks are vulnerable to input tampering, which in the real world could compromise the safety of autonomous vehicles. The problem would be amplified even more when uncertainty errors could not propagate into the submodules, if these are not a part of the end-to-end system design. To address these concerns, a parallel module which verifies the predictions of the object proposals coming out of Deep Neural Networks are required. This work aims to verify 3D object proposals from MonoRUn model by proposing a plausibility framework that leverages cross sensor streams to reduce false positives. The verification metric being proposed uses prior knowledge in the form of four different energy functions, each utilizing a certain prior to output an energy value leading to a plausibility justification for the hypothesis under consideration. We also employ a novel two-step schema to improve the optimization of the composite energy function representing the energy model

Developing a proof of principle 3D-printed lab-on-a-disc assay platform.

A 3D-printed microfluidic lab-on-a-disc (LOAD) device was designed and manufactured using a low cost (˜£1600) consumer grade fused deposition modelling (FDM) Ultimaker 2+ 3D printer with imbedded microfluidic channels 1 mm wide, 400 μm depth and with a volumetric capacity of approximate 23 μl. FDM printers are not typically used, or are capable, of producing the fine detailed structures required for microfluidic fabrication; in addition 3D-printed objects can suffer from poor optical transparency. However, in this work, imbedded microfluidic channels were produced and the optical transparency of the device was improved though manufacture optimisation to such a point that optical colourimetric assays can be performed in a microfluidic cuvette device with sample path length of 500 μm and volumetric capacity of 190 μl. When acetone vapour treatment was used, it was possible to improve transparency of plastic samples by up to a further 30%. The LOAD device is capable of being spun using an unmodified optical disc drive (ODD), demonstrating the centrifugation based separation of plasma from whole blood in a low-cost FDM 3D-printed microfluidic LOAD device. A cholesterol assay and glucose assay was developed and optimised using cholesterol oxidase (ChOx) or glucose oxidase (GlOx) respectively and horseradish peroxidase (HRP) for the oxidative coupling of chromotropic acid (CTA) and 4-aminoantipyrine (AAP). This produced a blue quinoneimine dye with a broad absorbance peaking at 590 nm for the quantification of cholesterol/glucose in solution. The colourimetric enzymatic cascade assays were developed for use within low-cost FDM 3D-printed microfluidic devices to demonstrate the capabilities and functionality of the devices. For comparison, the assay was run in standard 96 well plates with a commercial plate reader. The results demonstrated that the quantification of 0-10 mM glucose solution using a 3D-printed microfluidic optical device had a performance comparable to a plate reader assay; glucose assay in whole blood samples R² = 0.96

Epälambertilaiset pinnat ja niiden haasteet konenäössä

This thesis regards non-Lambertian surfaces and their challenges, solutions and study in computer vision. The physical theory for understanding the phenomenon is built first, using the Lambertian reflectance model, which defines Lambertian surfaces as ideally diffuse surfaces, whose luminance is isotropic and the luminous intensity obeys Lambert's cosine law. From these two assumptions, non-Lambertian surfaces violate at least the cosine law and are consequently specularly reflecting surfaces, whose perceived brightness is dependent from the viewpoint. Thus non-Lambertian surfaces violate also brightness and colour constancies, which assume that the brightness and colour of same real-world points stays constant across images. These assumptions are used, for example, in tracking and feature matching and thus non-Lambertian surfaces pose complications for object reconstruction and navigation among other tasks in the field of computer vision. After formulating the theoretical foundation of necessary physics and a more general reflectance model called the bi-directional reflectance distribution function, a comprehensive literature review into significant studies regarding non-Lambertian surfaces is conducted. The primary topics of the survey include photometric stereo and navigation systems, while considering other potential fields, such as fusion methods and illumination invariance. The goal of the survey is to formulate a detailed and in-depth answer to what methods can be used to solve the challenges posed by non-Lambertian surfaces, what are these methods' strengths and weaknesses, what are the used datasets and what remains to be answered by further research. After the survey, a dataset is collected and presented, and an outline of another dataset to be published in an upcoming paper is presented. Then a general discussion about the survey and the study is undertaken and conclusions along with proposed future steps are introduced