Le Modèle Nominatif de Régions : segmentation couleur et identification de régions par analyse de couleur et de texture

Nous nous intéressons ici au développement des capacités de perception d'un robot mobile destiné à evoluer en environnement naturel (extérieur). Dans ce cadre, la connaissance du terrain ou des objets situés dans l'environnement peut être améliorée en ajoutant des informations autres que géométriques, telles que la couleur et la texture. Nous avons proposé comme représentation complémentaire, le modèle nominatif de régions qui indique la nature de chaque région d'une image. Un algorithme de segmentation couleur donne une description très synthétique de la scène. Les régions issues de cette segmentation sont ensuite caractérisées par leur couleur et leur texture puis identifiées en utilisant une technique probabiliste afin d'obtenir leur nature (roche, herbe, terre ... )

Virtual Reality Sickness Reduces Attention During Immersive Experiences

In this paper, we show that Virtual Reality (VR) sickness is associated with a reduction in attention, which was detected with the P3b Event-Related Potential (ERP) component from electroencephalography (EEG) measurements collected in a dual-task paradigm. We hypothesized that sickness symptoms such as nausea, eyestrain, and fatigue would reduce the users' capacity to pay attention to tasks completed in a virtual environment, and that this reduction in attention would be dynamically reflected in a decrease of the P3b amplitude while VR sickness was experienced. In a user study, participants were taken on a tour through a museum in VR along paths with varying amounts of rotation, shown previously to cause different levels of VR sickness. While paying attention to the virtual museum (the primary task), participants were asked to silently count tones of a different frequency (the secondary task). Control measurements for comparison against the VR sickness conditions were taken when the users were not wearing the Head-Mounted Display (HMD) and while they were immersed in VR but not moving through the environment. This exploratory study shows, across multiple analyses, that the effect mean amplitude of the P3b collected during the task is associated with both sickness severity measured after the task with a questionnaire (SSQ) and with the number of counting errors on the secondary task. Thus, VR sickness may impair attention and task performance, and these changes in attention can be tracked with ERP measures as they happen, without asking participants to assess their sickness symptoms in the moment

A homicidal differential drive robot

Abstract—In this paper, we consider the problem of captur-ing an omnidirectional evader using a Differential Drive Robot in an obstacle free environment. At the beginning of the game the evader is at a distance L> l from the pursuer. The pursuer goal is to get closer from the evader than the capture distance l. The goal of the evader is to keep the pursuer at all time farther from it than this capture distance. In this paper, we found closed-form representations of the motion primitives and time-optimal strategies for each player. These strategies are in Nash Equilibrium, meaning that any unilateral deviation of each player from these strategies does not provide to such player benefit toward the goal of winning the game. We also present the condition defining the winner of the game and we construct a solution over the entire reduced space. I

Optimal paths for landmark-based navigation by differential-drive vehicles with field-of-view constraints

Abstract—In this paper, we consider the problem of planning optimal paths for a differential-drive robot with limited sensing, that must maintain visibility of a fixed landmark as it navigates in its environment. In particular, we assume that the robot’s vision sensor has a limited field of view (FOV), and that the fixed landmark must remain within the FOV throughout the robot’s motion.We first investigate the nature of extremal paths that satisfy the FOV constraint. These extremal paths saturate the camera pan angle. We then show that optimal paths are composed of straight-line segments and sections of these these extremal paths. We provide the complete characterization of the shortest paths for the system by partitioning the plane into a set of disjoint regions, such that the structure of the optimal path is invariant over the individual regions. Index Terms—Nonholonomic constraints, optimal control. I

A Sampling-Based Motion Planning Approach to Maintain Visibility of Unpredictable Targets

This paper deals with the surveillance problem of computing the motions of one or more robot observers in order to maintain visibility of one or several moving targets. The targets are assumed to move unpredictably, and the distribution of obstacles in the workspace is assumed to be known in advance

Path Planning for a Differential Drive Robot: Minimal Length Paths-A Geometric Approach

{ sbhattac, mumeta, setb} @ uiuc.edu Abstract- This work presents the minimal length paths, for a robot that maintains risibility of a landmark. The robot is a differential drive system and has limited sensing capabilities (range and angle of view). The optimal paths are eomposed of straight liner and curves that saturate Le Camera pan angle. I

Optimal Motion Strategies Based on Critical Events to Maintain Visibility of a Moving Target

In this paper, we consider the surveillance problem of maintaining visibility at a fixed distance of a mobile evader using a mobile robot equipped with sensors

Planning Expected-time Optimal Paths for Searching Known Environments

In this paper we address the problem of finding time optimal search paths in known environments. In particular, the task is to search a known environment for an object whose unknown location is characterized by a known probability density function (pdf). With this formulation, the time required to find the object is a random variable induced by the choice of search path together with the pdf for the object's location. The optimization problem is to find the path that yields the minimum expected value of the time required to find the object. We propos