Roland Chapuis

• PhD
• Professor (Full) at University of Clermont Auvergne

Evaluating the risk associated with operations is an essential element of safe planning and an essential prerequisite in mobile robotics. This issue is very broad, with numerous definitions emerging in the recent literature adapting different application scenarios and leading to different algorithmic approaches. In this review, we will investigate...

The basic functions of an autonomous vehicle typically involve navigating from one point to another in the world by following a reference path and analyzing the traversability along this path to avoid potential obstacles. What happens when the vehicle is subject to uncertainties in its localization? All its capabilities, whether path following or o...

In the context of autonomous vehicles on highways, one of the first and most important tasks is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take into account the information from several sensors and fuse them with data coming from road maps. The localization problem on highways can be distilled into three...

In the context of autonomous robots, one of the most important tasks is to prevent potential damage to the robot during navigation. For this purpose, it is often assumed that one must deal with known probabilistic obstacles, then compute the probability of collision with each obstacle. However, in complex scenarios or unstructured environments, it...

To navigate safely and efficiently, a robot must be aware of its surroundings. Although Bayesian occupancy grids are an efficient way to map the environment, they are not well-suited to assess risks of a specific path. In this paper, we extend the work of Laconte et al. [1] to generate meaningful risks in 3D environments. Here, we define the risk a...

In the context of autonomous vehicles, one of the most crucial tasks is to estimate the risk of the undertaken action. While navigating in complex urban environments, the Bayesian occupancy grid is one of the most popular types of map, where the information of occupancy is stored as the probability of collision. Although widely used, this kind of r...

Automotive players have recently shown an increasing interest in high-precision mapping, with the aim of enhancing vehicles safety and autonomy. Nevertheless, the acquisiton, processing and updates of accurate maps remains an economic challenge. Collaborative mapping through vehicles crowdsourcing represents a promising solution to tackle this prob...

Automotive players have recently shown an increasing interest in high-precision mapping, with the aim of enhancing vehicles safety and autonomy. Nevertheless, the acquisiton, processing and updates of accurate maps remains an economic challenge. Collaborative mapping through vehicles crowdsourcing represents a promising solution to tackle this prob...

Localizing the vehicle in its lane is a critical task for any autonomous vehicle. By and large, this task is carried out primarily through the identification of ego-lane markings. In recent years, ego-lane marking detection systems have been the subject of various research topics, using several inputs data such as camera or lidar sensors. Lately, t...

Locating the vehicle in its road is a critical part of any autonomous vehicle system and has been subject to different research topics. In most of the works presented in the literature, ego-localization is split into three parts: Road level-localization: the road on which the vehicle travels, Lane level localization: the lane on which the vehicle t...

Automotive players have recently shown an increasing interest in high-precision mapping, with the aim of enhancing vehicles safety and autonomy. Nevertheless, the acquisition, processing, and updates of accurate maps remains an economic challenge. Collaborative mapping through vehicles crowdsourcing represents a promising solution to tackle this pr...

Automotive players have recently shown an increasing interest in high-precision mapping, with the aim of enhancing vehicles safety and autonomy. Nevertheless, the acquisition, processing, and updates of accurate maps remains an economic challenge. Collaborative mapping through vehicles crowdsourcing represents a promising solution to tackle this pr...

For connected vehicles to have a substantial effect on road safety, it is required that accurate positions and trajectories can be shared. To this end, all vehicles must be accurately geolocalized in a common frame. This can be achieved by merging GNSS (Global Navigation Satellite System) information and visual observations matched with a map of ge...

For connected vehicles to have a substantial effect on road safety, it is required that accurate positions and trajectories can be shared. To this end, all vehicles must be accurately geolocalized in a common frame. This can be achieved by merging GNSS (Global Navigation Satellite System) information and visual observations matched with a map of ge...

In this article, we present a parsimonious high level multi-sensor fusion architecture for robot localization using several types of localization techniques. Operating in a Top-Down mode, the parsimonious localization system based on the use of an existing absolute environment map, selects the most adequate modality in an economical and efficient w...

In this paper we propose a method for accurate ego-lane localization using camera images, on-board sensors and lanes number information from OpenStreetMap (OSM). The novelty relies in the probabilistic framework developed, as we introduce a modular Bayesian Network (BN) to infer the ego-lane position from multiple inaccurate information sources. Th...

In a context of autonomous robots, one of the most important task is to ensure the safety of the robot and its surrounding. Most of the time, the risk of navigation is simply said to be the probability of collision. This notion of risk is not well defined in the literature, especially when dealing with occupancy grids. The Bayesian occupancy grid i...

In a context of autonomous robots, one of the most important task is to ensure the safety of the robot and its surrounding. Most of the time, the risk of navigation is simply said to be the probability of collision. This notion of risk is not well defined in the literature, especially when dealing with occupancy grids. The Bayesian occupancy grid i...

Road information, like lanes number, play an important role for intelligent vehicles (IV). Traditionally such road information are obtained through a vision-based measurement or by using a digital detailed map. In this paper, we present a new method for estimating the number of lanes using a low precision GPS receiver and OpenSteetMap (OSM). The me...

Vehicles are being equipped with more and more smart devices, which help the driver in his tasks. Alongside the trend to more and more autonomous vehicles emerges the possibility of making vehicles that move together as a platoon, which can be defined as a spatiooral organization of a set of vehicles based on a specific predetermined geometrical co...

In today's world, automatic navigation for a robotic device (autonomous vehicle and robot) is a pre-requisite for many complex tasks, which requires a robust localization method. We focus in this paper on the topic of localizing such a robot into an absolute and imprecise map. We propose a multi-sensor self-localization method, which is simultaneou...

In this article, a localization system for a mobile robot, using a top-down multisensors approach and a map of the environment, is proposed. Popular methods try to optimize a global cost, track multihypothesis, or reduce the problem by using multisensors. These approaches are bottom-up: Each sensor data is analyzed even if it is not relevant [like...

As robots leave the simple and static environments to more complex and dynamic ones, they will have to improve their localisation abilities and to deal with heterogeneous and imprecise data. In this paper, we present a general cooperative framework designed to localize in an absolute way a fleet of heterogeneous vehicles. Depending on the sensors i...

Multiple-object tracking constitutes a major step in several computer vision applications, such as surveillance, advanced driver assistance systems, and automatic traffic monitoring. Because of the number of cameras used to cover a large area, these applications are constrained by the cost of each node, the power consumption, the robustness of the...

Technology is rapidly changing and the automotive world is constantly improving. One of the challenges for automotive industry is to develop the completely autonomous car. Even if proven feasible, the autonomous driving car is still an important research subject due to systems complexity, costs and legislation. The paper describes an experimental c...

In this paper, a multi-object tracking system designed for a low cost embedded smart camera is proposed. Objects tracking constitutes a main step in video-surveillance applications. Because of the number of cameras used to cover a large area, surveillance applications are constrained by the cost of each node, the power efficiency of the system, the...

Localization without prior knowledge can be a difficult task for a vehicle. An answer to this problematic lies in the Simultaneous Localization And Mapping (SLAM) approach where a map of the surroundings is built while simultaneously being used for localization purposes. However, SLAM algorithms tend to drift over time, making the localization inco...

The localization of a vehicle in an unknown environment is often solved using simultaneous localization and mapping (SLAM) techniques. Many methods have been developed, each requiring a different amount of landmarks (map size), and thus of memory, to work efficiently. Similarly, the required computational time is quite variable from one approach to...

In this paper, we propose a new approach to the decentralized Simultaneous Localization And Mapping (SLAM) problem. The goal is to demonstrate the feasibility of decentralized localization using low-density maps built with low-cost sensors. This problem is challenging at different levels. Indeed, each vehicle localization tends to drift over time i...

In this paper1, a localization system for a mobile robot is proposed, using a top-down multi-sensorial approach and exploiting a map of the environment. Generally, the data sensors are associated with the map by a classical map-matching process. Because of the embedded sensors, the field of view is limited, there is a risk of false association betw...

In this paper, we propose a vision tracking system primarily targeted for systems with low computing resources. It is based on GMPHD filter and can deal with occlusion between objects. The proposed algorithm is supposed to work in a node of camera network where the cost of the computer processing the information is critical. To achieve a low comput...

In this paper, a localization system for a mobile robot is proposed, using a top-down multi-sensorial approach and exploiting a map of the environment. Nowadays the wide development of maps make relevant localization approachesable to use such maps. A crucial point of all localization systems is the way of the data provided by different sensors are...

This paper investigates the Multi-Target Tracking (MTT) for embedded systems. Many real-time tracking applications, like surveillance with Unmanned Aerial Vehicle (UAV), objects tracking with smart phones or smart cameras, require the use of embedded systems that are constrained by the size and the energy consumption of the calculator. However, the...

L'intégration du comportement humain dans le processus d'un robot peut fortement accroître ses capacités, notam-ment dans le cas d'actions guidées par des objectifs précis et la topologie de l'environnement. L'approche proposée ici présente un système de localisation pour un robot mobile exploitant de manière active à la fois les capteurs dont il d...

Today, the problem of designing suitable multiprocessor architecture tailored for a target application field raises the need for a fast and efficient multiprocessor system-on-chip (MPSoC) design environment. Additionally, the implementation of image processing applications on MPSoC system will need to exploit the parallelism and the pipelining in a...

This paper presents a solution to the consistency problem of SLAM algorithms. We propose here to model the drift affecting the estimation process. The divergence is seen as a bias on the vehicle localization. By using such a model, we are able to guarantee the consistency of the localization. We developed a filter taking into account the divergence...

In this paper, the problem of targets road tracking, like pedestrians and vehicles tracking is addressed. This paper proposes to improve a Cardinalized Probability Hypothesis Density (CPHD) filter in presence of occlusion using the sensor classification of each targets detected. Using this classification, a probability of target type is computed by...

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Rotating radar sensors are perception systems rarely used in mobile robotics. This paper is concerned with the use of a mobile ground-based panoramic radar sensor which is able to deliver both distance and velocity of multiple targets in its surrounding. The consequence of using such a sensor in high speed robotics is the appearance of both geometr...

In this paper, the problem of targets road tracking based on multiple asynchronous sensors is addressed. A method based on Cardinalized Probability Hypothesis Density (CPHD) filter improved with probability of target type is presented. Using the sensor classification, the probability of target type is recursively computed by Bayesian rules. This pr...

Abstract This paper is concerned with robotic applications using a ground‐based radar sensor for simultaneous localization and mapping problems. In mobile robotics, radar technology is interesting because of its long range and the robustness of radar waves to atmospheric conditions, making these sensors well‐suited for extended outdoor robotic app...

This paper presents a multi-vehicle decentralized SLAM algorithm. We expose the different problems involved by this decentralized setting, such as network aspects (data losses, latencies or bandwidth requirements) or data incest (double-counting information), and address them. In order to ease the data association process and also guarantee the con...

Résumé— Le projet IMPALA s'effectue dans le cadre d'une collaboration scientifique entre deux structures de recherche et un industriel : le LASMEA, le Cemagref et THALES. Il porte sur l'utilisation d'un radar panoramique hyperfréquence pour des applications de localisation et de cartographie simultanées en milieu extérieur (connu sous l'acronyme an...

This paper presents a real-time Decentralized Monocular SLAM process. It is the first time, to our knowledge, that a decentralized SLAM with vehicles using only proprioceptive sensors and a single camera is presented. A new architecture has been built to cope with the problems involved by a decentralized scheme. A special care has been given to the...

In this article, we present a new multistage architecture oriented to real-time complex processing applications. Given a set of rules, this proposed architecture allows the using of different communication links (point to point link, hardware router…) to connect unlimited number of parallel computing elements (software processors) to follow the inc...

This paper presents a real time monocular EKF SLAM process that uses only Cartesian defined landmarks. This representation is easy to handle, light and consequently fast. However, it is prone to linearization errors which can cause the filter to diverge. Here, we will first clearly identify and explain when those problems take place. Then, a soluti...

In this paper, we present a robust approach to occlusion problems for tracking vehicle and pedestrian on road context. Most multi-target tracking algorithms, like Multiple Hypothesis Tracker (MHT) or Cardinalized Probability Hypothesis Density (CPHD), are based on a sensor detection probability map. This paper proposes to solve the occlusion issue...

The Multiple Hypothesis Tracker (MHT) and the Cardinalized Probability Hypothesis Density (CPHD) are two algorithms which can overcome the Multi-Targets Tracking (MTT) issues in automotive applications. This paper describes the performance of such algorithms and, in particular the Gaussian Mixture Probability Hypothesis Density (GMPHD) filter and t...

The use of a rotating range sensor in high speed robotics creates distortions in the collected data. Such an effect is, in the majority of studies, ignored or considered as noise and then corrected, based on proprioceptive sensors or localization systems. In this study we consider that distortion contains the information about the vehicle's displac...

The detection and tracking of moving objects (DATMO) in an outdoor environment from a mobile robot are difficult tasks because of the wide variety of dynamic objects. A reliable discrimination of mobile and static detections without any prior knowledge is often conditioned by a good position estimation obtained using Global Positionning System/Diff...

Résumé L'utilisation d'un capteur télémétrique tournant en robo-tique mobile à haute vitesse implique l'apparition de dis-torsions sur les données collectées. Un tel effet est, dans la majorité des études, ignoré ou considéré comme un bruit et, de ce fait, corrigé en utilisant des capteurs propriocep-tifs ou des systèmes de localisation. Dans cet a...

This paper presents a robust hybrid approach to Predictive Lane Detection - PLD, which utilizes information from digital map to improve efficiency and accuracy to vision-based lane detector. Traditional approaches are mostly designed for well maintained and simple road conditions like motorway or interstate road with clear lane markers, to solve ou...

Le projet IMPALA rattaché à l’appel à projets PSIROB 2006 de l’Agence Nationale de la Recherche réunit deux structures de recherche et un industriel : IRSTEA, le LASMEA et THALES Optronique. L’objectif du projet est d’évaluer l’apport du radar comme solution alternative aux moyens de perception en robotique mobile d’extérieur. Cet article illustre...

This article deals with the divergence of the Kalman filter when used on non-linear observation functions. The Kalman filter allows to update some parameters according to observations and their uncertainties. The observation model which links the parameters to the observations is often non-linear and has to be linearized. An improper linearization...

This paper is concerned with the Simultaneous Localization And Mapping (SLAM) application with a mobile robot moving in a structured environment using data obtained from rotating sensors such as radars or lasers. A line-based EKF-SLAM (EKF stands for Extended Kalman Filter) algorithm is presented, which is able to deal with data that cannot be cons...

This paper is about environment perception for navigation system in outdoor applications. Unlike other approaches that try to detect an obstacle of binary state, we consider here a Digital Elevation Map (DEM). This map has to be built in regards to the guidance system's needs. These needs depend on the vehicle capabilities, its dynamics constraints...

In this paper, a state exchange based multi-robot localization is proposed in particular experiments in real conditions. The goal of such an approach is to combine the data coming from several mobile communicating robots in order to i) update and maintain in each robot an optimal map of the whole fleet, and ii) improve all the poses estimation taki...

In this article we address the problem of the traversability of the trajectory of an agricultural robot defining the conditions insuring a safe displacement according the notion of "obstacle". Unlike other approaches that try to detect and to avoid obstacle, we propose the concept of Allowable Speed Trajectories which depends on the vehicle capabil...

This paper is about environment perception for nav-igation system in outdoor applications. Unlike other approaches that try to detect an obstacle of binary state, we consider here a Digital Elevation Map (DEM). This map has to be built in regards to the guidance system's needs. These needs depend on the vehicle capabilities, its dynamics constraint...

In this paper, we address the problem of robust data association in active search for simultaneous vehicle localization and path tracking. We show that the classical landmarks active search approach, which consists in focusing processing resources on windows-of-interest where landmarks are supposed to be, is weak when faced with wrong data associat...

In this chapter, we have presented a method to improve localization systems based to data association with GNSS receiver. This method increases the precision and the reliability of localization based on an Kalman filter. It consists to take care the characteristics of GNSS error. This error is an unpredictive stochastic process and it drifts the es...

This paper is about preservation of physical integrity of mobile robot for real outdoor applications encountered in agricultural field. Unlike other approaches that try to detect and to avoid obstacle, we consider the allowable speed grid. This grid depends on the vehicle capabilities, its dynamic constraints, its speed and the 3D rendering of the...

This paper is about environment perception for navigation system in real outdoor applications. Unlike other approaches that try to detect an obstacle of binary state, we consider here a Digital Elevation Map (DEM). This map has to be built in regards to the guidance system's needs. These needs depend on the vehicle capabilities, its dynamical const...

This article deals with mobile robotics in convoy. An autonomous vehicle has to follow the path of the vehicle ahead of it, but without having the vehicle ahead in its field of view. So, the task for the second vehicle is to follow the leader's path with a variable time delay. Moreover, relatively strong constraints are imposed in terms of speed of...

This paper is concerned with the simultaneous localization and mapping (SLAM) application using data obtained from a microwave radar sensor. The radar scanner is based on the frequency modulated continuous wave (FMCW) technology. In order to overcome the complexity of radar image analysis, a trajectory-oriented EKF-SLAM technique using data from a...

This paper describes how multisensor data fusion increases reliability of pedestrian classification while using a Bayesian approach. The proposed approach fuses information provided by a laser range scanner and a monocular grey-level camera. Fusion is applied at feature level by using sets of related features and possibly correlation sensor observa...

This paper is concerned with the Simultaneous Localization And Mapping (SLAM) problem using data obtained from a microwave radar sensor. The radar scanner is based on Frequency Modulated Continuous Wave (FMCW) technology. In order to meet the needs of radar image analysis complexity, a trajectoryoriented EKF-SLAM technique using data from a 360. fi...

The principle of a vision system based on a progressive focus of attention principle is presented. This approach considers the visual recognition strategy as an estimation problem for which the purpose is to estimate both precisely and reliably the parameters of the object to be recognized. The object is constituted of parts statistically dependent...

We have previously proposed a Bayesian framework to fuse at feature level information from a lidar and video camera in order to classify pedestrians. After studying the influence of each stage of the computation on the system performance, it appears that object segmentation and sensor models are essential for good results. In this paper, we propose...

This communication presents the comparison of two data fusion methods : the extended Kalman filter and the constraint manifold particle filter applied to the problem of vehicle positioning estimation. The comparison is made with reference to precise positioning data given by a differential GPS. The estimation fuses natural GPS data of metric precis...

The evolution of population needs, together with the necessity of envi-ronment preservation, rise important issues related to the way the human produc-tion have to progress. It is for instance the case in agriculture area, where the pro-duction have to increase in order to feed a growing population, while the environ-mental damage must decrease. Si...

This paper deals with using of low-cost Global Navigation Satellite System (GNSS) sensors in a localization process for an autonomous guidance system of mobile robots. Generally, this process is made using a Kalman Filter (KF) to fuse information coming from different sensors. But as GNSS error is an unpredictable stochastiscal process, the localiz...

This paper considers the problem of the classification of objects observed by vehicle embedded sensors. We propose a general architecture and an algorithm to perform multisensor fusion for the classification purpose. The proposed solution has to be robust and flexible. The robustness is essential because this system is for safety applications. The...

This paper describes how multisensor data fusion increases reliability of pedes-trian detection while using a Bayesian combination of features. The clue is to combine in a probabilistic framework, the detecting capabilities of sensors for identifying pedestrians located along the vehicle trajectory. The work emphasizes the idea of redundancy due to...

To guide a vehicle, the localization system must provide an accurate and reliable estimation. Generally, the estimation of the vehicle's state is dealt with a Bayesian approach like a Kalman filter. However, if this technique is a good mean to merge information of different sensors, it gives any idea of the result's reliability. We propose here to...

In this paper, we make an analysis of map aided localization systems (MAL) in noisy outdoor environments. In a first time, we present the main sensors used in those approaches and their behavior in noisy environments. We notice that sensors don't offer the same performance. In MAL approaches, those sensors are used to detect landmarks. This detecti...

Markov localization is one of the effective techniques for determining the physical locations of an autonomous vehicle whose the perceptions of the environment are limited. To improve the localization, a multi-sensor approach is used. A landmark selection process is usually employed. The aim of this selection strategy is to select the landmark that...

Improvements on pedestrian classification reliability applying a Bayesian approach to multisensor data fusion is described in this paper. The proposed approach fuses information provided by a laser scanner and a monocular gray-level camera. The key is to combine in a probabilistic framework, the detecting capabilities of these sensors to classify p...

This paper considers the problem of cooperative localization of an heterogeneous group of road vehicles. Each vehicle can be equipped with proprioceptive and exteroceptive sensors enabling it to localize itself in its environment and also to localize (but not to identify) the other members of the group. Localization information can be exchanged bet...