Multi-target detection and recognition by UAVs using online POMDPs

This paper tackles high-level decision-making techniques for robotic missions, which involve both active sensing and symbolic goal reaching, under uncertain probabilistic environments and strong time constraints. Our case study is a POMDP model of an online multi-target detection and recognition mission by an autonomous UAV.The POMDP model of the multi-target detection and recognition problem is generated online from a list of areas of interest, which are automatically extracted at the beginning of the flight from a coarse-grained high altitude observation of the scene. The POMDP observation model relies on a statistical abstraction of an image processing algorithm's output used to detect targets. As the POMDP problem cannot be known and thus optimized before the beginning of the flight, our main contribution is an ``optimize-while-execute'' algorithmic framework: it drives a POMDP sub-planner to optimize and execute the POMDP policy in parallel under action duration constraints. We present new results from real outdoor flights and SAIL simulations, which highlight both the benefits of using POMDPs in multi-target detection and recognition missions, and of our`optimize-while-execute'' paradigm

Report on Accident Analysis, Deliverable 3.2.3 of the EC FP7 Project CASPER (2012)

This document reports on work undertaken in subtasks 3.2.2 (Focussed accident data collection) and 3.2.4 (Data analysis and reporting) of the EC CASPER (Child Advanced Safety Project for European Roads) project. There are two main objectives, to describe the information available from the road accident data collection activity of the CASPER project and its predecessors, CREST and CHILD, and to provide an analysis of the child accident data – within the constraints of the case selection criteria used. This work would not be possible without the contributions made to the road accident database by the participants in all three EC projects (CREST, CHILD and CASPER) – the data collection teams and sponsors of the data collection activities

Validation of real-time properties of a robotic software architecture

National audienceIn this paper, we propose a mechanism allowing to evaluate the schedulability of a robotic software architecture, and then validate its real-time properties. The robotic software architecture is described through a Domain Specific Language (DSL), MAUVE, that allows to model communicating components. The evaluation of schedulability of the architecture consists in first computing the Worst-Case Execution Time (WCET) of the elementary functions of the components. Then the Worst Case Response Time (WCRT) of the component is computed from the elementary WCET and the component models, allowing to validate the schedulatiblity of the architecture. We illustrate our methodology on the evaluation of a control architecture for a ground mobile robot

Un module de gestion de mission autonome pour des satellites d'observation de la Terre

International audienceThis paper presents an autonomous controller developed for managing the activities of a new generation of Earth Observing Satellites (EOSs). This controller uses a hierarchy of reactors as in previously existing architectures, and it exploits specific r easoning p rocedures a t t he l evel o f e ach r eactor to get fast deliberations on-board. It is able to take into account the arrival of urgent acquisition requests, late cloud predictions , and information about the real volume of data, while meeting several operational requirements from the end-users

Mauve: a Component-based Modeling Framework for Real-time Analysis of Robotic Applications.

Robots are more and more used in very diverse situations (services to persons, military missions, crisis management, . . . ) in which robots must give some guarantees of safety and reliability. To be really integrated in everyday life, robots must fulfil some requirements. Among these requirements, we focus on the nonfunctional requirements on embedded software [1], and more specifically on real-time software requirements. These requirements are most of the time fulfilled by proving the schedulability of the embedded software. Analysing and validating such properties on an existing hand-coded software requires some reverse modelling of the software, leading to approximations of its behaviour. These approximations may have certification authorities not be confident on the robot dependability. This paper proposes an integrated development methodology that starts from software component modelling, and leads to both validation of the embedded software and generation of deployable embedded software

Détection et reconnaissance de cibles en ligne pour des UAV autonomes avec un modèle de type POMDP

Cet article présente une mission pour la détection et reconnaissance de cibles menée par un véhicule aérien inhabité (UAV) autonome. La mission est modélisée par un Processus de Markov Partiellement Observable (POMDP). Le modèle POMDP traite dans un cadre unique des actions de perception (comme l'angle de prise de vue de la caméra) et des actions qui mènent à l'accomplissement de la mission (changement de zone, altitude de vol, atterrissage). La mission consiste à atterrir dans la zone qui contient une voiture dont le modèle reconnu est celui recherché, avec un état de croyance suffisant. Nous expliquons comment nous avons appris le modèle d'observation probabiliste du POMDP à partir d'une étude statistique des sorties de l'algorithme de traitement d'image. Cet algorithme utilisé pour reconnaître des objets dans la scène est embarquée sur notre UAV. Nous présentons aussi notre cadre \emph{optimize-while-executing}, qui administre un sous-planificateur POMDP pour optimiser et exécuter en parallèle la politique avec des contraintes de temps associées à la durée des actions, et qui raisonne sur les états futurs possibles du système robotique. Finalement, nos résultats expérimentaux sont présentés. Ils démontrent que des techniques d'intelligence artificielle comme les POMDP peuvent être appliquées avec succès pour contrôler automatiquement des actions de perception et d'accomplissement de mission pour des missions complexes en temps contraint pour un UAV autonome

POMDP-based online target detection and recognition for autonomous UAVs

This paper presents a target detection and recognition mission by an autonomous Unmanned Aerial Vehicule (UAV) modeled as a Partially Observable Markov Decision Process (POMDP). The POMDP model deals in a single framework with both perception actions (controlling the camera's view angle), and mission actions (moving between zones and flight levels, landing) needed to achieve the goal of the mission, i.e. landing in a zone containing a car whose model is recognized as a desired target model with sufficient belief. We explain how we automatically learned the probabilistic observation POMDP model from statistical analysis of the image processing algorithm used on-board the UAV to analyze objects in the scene. We also present our "optimize-while-execute" framework, which drives a POMDP sub-planner to optimize and execute the POMDP policy in parallel under action duration constraints, reasoning about the future possible execution states of the robotic system. Finally, we present experimental results, which demonstrate that Artificial Intelligence techniques like POMDP planning can be successfully applied in order to automatically control perception and mission actions hand-in-hand for complex time-constrained UAV missions

Method and device for detecting piloting conflicts between the crew and the autopilot of an aircraft

According to the invention, the method comprises checking that the actual values of navigation parameters become closer to desired values within a predetermined time period. If this is not the case, the method comprises carrying out a predictive calculation of the value of at least one particular parameter at consecutive future moments, and optionally transmitting an alarm for the crew

Child car passenger fatalities – European figures and in-depth study

This paper reports on three approaches undertaken to study overall child car passenger fatality numbers across Europe and examine conditions when fatalities occur. Firstly, a literature review of previous specific studies and public data finds data from WHO for estimating the relevance of child road accident fatalities. Detail for child fatalities as car passengers is found to be limited and for the future it is important to collect and harmonise exposure data (especially distance travelled) to compare countries and different modes of traffic for their fatality risk. Secondly, interrogation of the EC CARE database (Community database on Accidents on the Roads in Europe) for child car passenger fatalities finds that 392 children (0 to 13 years) were killed as car (or taxi) passengers in 23 countries of the EU during 2008, 44% of all road fatalities for this age group. Over the previous 10 year period the reduction in child car passenger fatalities is estimated to be 50% for the EU-19 countries with available data. Thirdly, in depth analysis of French police child passenger fatality files has taken place. The CASIMIR project (Child Accident Study Investigating Mortal Incident on the Road), the collation and in-depth analysis of French police child passenger fatality files from 2001 to 2003, was reported at FISITA 2010. An update of this study with data from 2005 to 2010 is on-going, in order to see if there are some evolutions (for example, new child restraint systems, new generation of cars and changes in parents’ behaviour) and more than 250 fatal accidents will be included in the 2nd phase. From previous results, frontal and side impacts remain a priority, with a small proportion killed in rear impacts and fatalities in roll-overs mostly unrestrained. In this kind of study there are some limits on the information regarding the quality of use of the restraint systems. Therefore a sample of 60 accidents was investigated in-depth (mostly front and side impacts) with special attention paid to the quality of restraint use. Results of these in depth investigations are reported in the present paper. The complete data of the 2nd phase of the CASIMIR project, also considering sociological data, will be published when all fatal accidents for the period have been coded. Parts of this work have been undertaken in the EC CASPER project and are reported in Deliverable 3.2.1 (Kirk et al, 2011). The activities regarding the French police fatal files have been undertaken in both the CASIMIR project and CASPER