Practical visual odometry for car-like vehicles

A method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to Ackerman's steering model is presented. By taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. The method has been implemented successfully on a large industrial forklift and a Toyota Prado SUV. Results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.

IMU aided 3D visual odometry for car-like vehicles

We present a method for calculating odome- try in three-dimensions for car-like ground ve- hicles with an Ackerman-like steering model. In our approach we use the information from a single camera to derive the odometry in the plane and fuse it with roll and pitch informa- tion derived from an on-board IMU to extend to three-dimensions, thus providing odometric altitude as well as traditional x and y transla- tion. We have mounted the odometry module on a standard Toyota Prado SUV and present results from a car-park environment as well as from an off-road track.

Visual servoing of a car-like vehicle - an application of omnidirectional vision

In this paper, we develop the switching controller presented by Lee et al. for the pose control of a car-like vehicle, to allow the use of an omnidirectional vision sensor. To this end we incorporate an extension to a hypothesis on the navigation behaviour of the desert ant, cataglyphis bicolor, which leads to a correspondence free landmark based vision technique. The method we present allows positioning to a learnt location based on feature bearing angle and range discrepancies between the robot's current view of the environment, and that at a learnt location. We present simulations and experimental results, the latter obtained using our outdoor mobile platform.

Vision-based navigational competencies for a car-like vehicle

If mobile robots are to perform useful tasks in the real-world they will require a catalog of fundamental navigation competencies and a means to select between them. In this paper we describe our work on strongly vision-based competencies: road-following, person or vehicle following, pose and position stabilization. Results from experiments on an outdoor autonomous tractor, a car-like vehicle, are presented.

Robust pose estimation for a car-like vehicle

In this paper, we outline the sensing system used for the visual pose control of our experimental car-like vehicle, the autonomous tractor. The sensing system consists of a magnetic compass, an omnidirectional camera and a low-resolution odometry system. In this work, information from these sensors is fused using complementary filters. Complementary filters provide a means of fusing information from sensors with different characteristics in order to produce a more reliable estimate of the desired variable. Here, the range and bearing of landmarks observed by the vision system are fused with odometry information and a vehicle model, providing a more reliable estimate of these states. We also present a method of combining a compass sensor with odometry and a vehicle model to improve the heading estimate.

Coverage algorithms for an under-actuated car-like vehicle in an uncertain environment

A coverage algorithm is an algorithm that deploys a strategy as to how to cover all points in terms of a given area using some set of sensors. In the past decades a lot of research has gone into development of coverage algorithms. Initially, the focus was coverage of structured and semi-structured indoor areas, but with time and development of better sensors and introduction of GPS, the focus has turned to outdoor coverage. Due to the unstructured nature of an outdoor environment, covering an outdoor area with all its obstacles and simultaneously performing reliable localization is a difficult task. In this paper, two path planning algorithms suitable for solving outdoor coverage tasks are introduced. The algorithms take into account the kinematic constraints of an under-actuated car-like vehicle, minimize trajectory curvatures, and dynamically avoid detected obstacles in the vicinity, all in real-time. We demonstrate the performance of the coverage algorithm in the field by achieving 95% coverage using an autonomous tractor mower without the aid of any absolute localization system or constraints on the physical boundaries of the area.

Optimum steering input determination and path-tracking of all-wheel steer vehicles on uneven terrains based on constrained optimization

In this paper we propose a framework for optimum steering input determination of all-wheel steer vehicles (AWSV) on rough terrains. The framework computes the steering input which minimizes the tracking error for a given trajectory. Unlike previous methodologies of computing steering inputs of car-like vehicles, the proposed methodology depends explicitly on the vehicle dynamics and can be extended to vehicle having arbitrary number of steering inputs. A fully generic framework has been used to derive the vehicle dynamics and a non-linear programming based constrained optimization approach has been used to compute the steering input considering the instantaneous vehicle dynamics, no-slip and contact constraints of the vehicle. All Wheel steer Vehicles have a special parallel steering ability where the instantaneous centre of rotation (ICR) is at infinity. The proposed framework automatically enables the vehicle to choose between parallel steer and normal operation depending on the error with respect to the desired trajectory. The efficacy of the proposed framework is proved by extensive uneven terrain simulations, for trajectories with continuous or discontinuous velocity profile.

Adaptive control system based on lineal control theory for the path-following problem of a car-like mobile robot

The objective of this paper is to design a path following control system for a car-like mobile robot using classical linear control techniques, so that it adapts on-line to varying conditions during the trajectory following task. The main advantages of the proposed control structure is that well known linear control theory can be applied in calculating the PID controllers to full control requirements, while at the same time it is exible to be applied in non-linear changing conditions of the path following task. For this purpose the Frenet frame kinematic model of the robot is linearised at a varying working point that is calculated as a function of the actual velocity, the path curvature and kinematic parameters of the robot, yielding a transfer function that varies during the trajectory. The proposed controller is formed by a combination of an adaptive PID and a feed-forward controller, which varies accordingly with the working conditions and compensates the non-linearity of the system. The good features and exibility of the proposed control structure have been demonstrated through realistic simulations that include both kinematics and dynamics of the car-like robot.

Sensing for visual homing

In this paper, we outline the sensing system used for the visual pose control of our experimental car-like vehicle, the Autonomous Tractor. The sensing system consists of a magnetic compass, an omnidirectional camera and a low-resolution odometry system. In this work, information from these sensors is fused using complementary filters. Complementary filters provide a means of fusing information from sensors with different characteristics in order to produce a more reliable estimate of the desired variable. Here, the range and bearing of landmarks observed by the vision system are fused with odometry information and a vehicle model, providing a more reliable estimate of these states. We also present a method of combining a compass sensor with odometry and a vehicle model to improve the heading estimate.

Product ecosystems : an emerging methodological approach to study the implementation of disruptive innovations : the case of the CityCar

The car has arguably had more influence on our lifestyle and urban environment than any other consumer product; allowing unprecedented freedom for living, working and recreation where and when we choose. However, problems of pollution, congestion, road trauma, inefficient land use and social inequality are associated with car use. Despite 100 years of design and technology refinements, the aforementioned problems are significant and persistent: many argue that resolving these problems requires a fundamental redesign of the car. Redesigned vehicles have been proposed such as the MIT CityCar and others such as the Renault Twizy, commercialized. None however have successfully brought about significant change and the study of disruptive innovation offers an explanation for this. Disruptive innovation, by definition, disrupts a market. It also disrupts the product ecosystem. The existing product ecosystem has co-evolved to support the conventional car and is not optimized for the new design: which will require a redesigned ecosystem to support it. A literature review identifies a lack of methodology for identifying the components of product ecosystems and the changes required for disruptive innovation implementation. This paper proposes such a methodology based on Design Thinking, Actor Network Theory, Disruptive Innovation and the CityCar scenarios.

Stability analysis of aperiodic messages scheduled in the dynamic segment of flex ray protocol

In a cyber physical system like vehicles number of signals to be communicated in a network system has an increasing trend. More and more mechanical and hydraulic parts are replaced by electronic control units and infotainment and multimedia applications has increased in vehicles. Safety critical hard real time messages and aperiodic messages communicated between electronic control units have been increased in recent times. Flexray is a high bandwidth protocol consisting of static segment for supporting hard real time messages and a dynamic segment for transmitting soft and non real time messages. In this paper, a method to obtain the stability region for the random arrival of messages in each electronic control units which is scheduled in the dynamic segment of Flexray protocol is presented. Number of mini slots available in the dynamic segment of Flexray restricts the arrival rate of tasks to the micro controllers or the number of micro controllers connected to the Flexray bus. Stability region of mathematical model of the system is compared with the Flexray protocol simulation results.

Nouvelle approche pour modifier le tropisme des vecteurs adénoviraux à l’aide de ligands bispécifiques

L’adénovirus a été étudié dans l’optique de développer de nouveaux traitements pour différentes maladies. Les vecteurs adénoviraux (AdV) sont des outils intéressants du fait qu’ils peuvent être produits en grandes quantités (1X1012 particules par millilitre) et de par leur capacité à infecter des cellules quiescentes ou en division rapide. Les AdVs ont subi bon nombre de modifications pour leur permettre de traiter des cellules tumorales ou pour transporter des séquences génétiques exogènes essentielles pour le traitement de maladies monogéniques. Toutefois, les faibles niveaux d’expression du récepteur primaire de l’adénovirus, le CAR (récepteur à l’adénovirus et au virus coxsackie), réduit grandement l’efficacité de transduction dans plusieurs tumeurs. De plus, certains tissus normaux comme les muscles n’expriment que très peu de CAR, rendant l’utilisation des AdVs moins significative. Pour pallier à cette limitation, plusieurs modifications ont été générées sur les capsides virales. L’objectif de ces modifications était d’augmenter l’affinité des AdVs pour des récepteurs cellulaires spécifiques surexprimés dans les tumeurs et qui seraient exempts dans les tissus sains avoisinant. On peut mentionner dans les approches étudiées: l’utilisation de ligands bispécifiques, l’incorporation de peptides dans différentes régions de la fibre ou la substitution par une fibre de sérotypes différents. Notre hypothèse était que les domaines d’interaction complémentaire (K-Coil et ECoil) permettraient aux ligands de s’associer aux particules virales et d’altérer le tropisme de l’AdV. Pour ce faire, nous avons inclus un domaine d’interaction synthétique, le K-Coil,dans différentes régions de la fibre virale en plus de générer des mutations spécifiques pour abolir le tropisme naturel. Pour permettre la liaison avec les récepteurs d’intérêt dont l’EGF-R, l’IGF-IR et le CEA6, nous avons fusionné le domaine d’interaction complémentaire, le E-Coil, soit dans les ligands des récepteurs ciblés dont l’EGF et l’IGF-I, soit sur un anticorps à un seul domaine reconnaissant la protéine membranaire CEA6, l’AFAI. Suite à la construction des différents ligands de même que des différentes fibres virales modifiées, nous avons determiné tout d’abord que les différents ligands de même que les virus modifiés pouvaient être produits et que les différentes composantes pouvaient interagir ensemble. Les productions virales ont été optimisées par l’utilisation d’un nouveau protocole utilisant l’iodixanol. Ensuite, nous avons démontré que l’association des ligands avec le virus arborant une fibre modifiée pouvait entraîner une augmentation de transduction de 2 à 21 fois dans différentes lignées cellulaires. À cause de la difficulté des adénovirus à infecter les fibres musculaires occasionnée par l’absence du CAR, nous avons cherché à savoir si le changement de tropisme pourrait accroître l’infectivité des AdVs. Nous avons démontré que l’association avec le ligand bispécifique IGF-E5 permettait d’accroître la transduction autant dans les myoblastes que dans les myotubes de souris. Nous avons finalement réussi à démontrer que notre système pouvait induire une augmentation de 1,6 fois de la transduction suite à l’infection des muscles de souriceaux MDX. Ces résultats nous amènent à la conclusion que le système est fonctionnel et qu’il pourrait être évalué dans des AdVs encodant pour différents gènes thérapeutiques.

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

Development and evaluation of a range anxiety-reducing business model for connected full electric vehicles

This thesis develops and evaluates a business model for connected full electric vehicles (FEV) for the European market. Despite a promoting political environment, various barriers have thus far prevented the FEV from becoming a mass-market vehicle. Besides cost, the most noteworthy of these barriers is represented by range anxiety, a product of FEVs’ limited range, lacking availability of charging infrastructure, and long recharging times. Connected FEVs, which maintain a constant connection to the surrounding infrastructure, appear to be a promising element to overcome drivers’ range anxiety. Yet their successful application requires a well functioning FEV ecosystem which can only be created through the collaboration of various stakeholders such as original equipment manufacturers (OEM), first tier suppliers (FTS), charging infrastructure and service providers (CISP), utilities, communication enablers, and governments. This thesis explores and evaluates how a business model, jointly created by these stakeholders, could look like, i.e. how stakeholders could collaborate in the design of products, services, infrastructure, and advanced mobility management, to meet drivers with a sensible value proposition that is at least equivalent to that of internal combustion engine (ICE) cars. It suggests that this value proposition will be an end-2-end package provided by CISPs or OEMs that comprises mobility packages (incl. pay per mile plans, battery leasing, charging and battery swapping (BS) infrastructure) and FEVs equipped with an on-board unit (OBU) combined with additional services targeted at range anxiety reduction. From a theoretical point of view the thesis answers the question which business model framework is suitable for the development of a holistic, i.e. all stakeholder-comprising business model for connected FEVs and defines such a business model. In doing so the thesis provides the first comprehensive business model related research findings on connected FEVs, as prior works focused on the much less complex scenario featuring only “offline” FEVs.