This thesis addresses the problem of energy management of a hybrid electric power unit for an autonomous vehicle. We introduce, evaluate, and discuss the idea of autonomous-specific energy management strategy. This method is an optimization-based strategy which improves the powertrain fuel economy by exploiting motion planning data. First, to build a firm base for further evaluations, we will develop a high-fidelity system-level model for our case study using MATLAB/Simulink. This model mostly concerns about energy-related aspects of the powertrain and the vehicle. We will derive and implement the equations for each of the model subsystems. We derive model parameters using available data in the literature or online. Evaluation of the developed model shows acceptable conformity with the actual dynamometer data. We will use this model to replace the built-in rule-based logic with the proposed strategy and assess the performance.\par Second, since we are considering an optimization-based approach, we will develop a novel convex representation of the vehicle and powertrain model. This translates to reformulating the model equations using convex functions. Consequently, we will express the fuel-efficient energy management problem as the convex optimization problem. We will solve the optimization problem using dedicated numerical solvers. Extracting the control inputs using this approach and applying them on the high-fidelity model provides similar results to dynamic programming in terms of fuel consumption but in substantially less amount of time. This will act as a pivot for the subsequent real-time analysis.\par Third, we will perform a proof-of-concept for the autonomous-specific energy management strategy. We implement an optimization-based path and trajectory planning for a vehicle in the simplified driving scenario of a racing track. Accordingly, we use motion planning data to obtain the energy management strategy by solving an optimization problem. We will let the vehicle to travel around the circuit with the ability to perceive and plan up to an observable horizon using the receding horizon approach. Developed approach for energy management strategy shows a substantial reduction in the fuel consumption of the high-fidelity model, compared to the rule-based controller. / Thesis / Master of Science in Mechanical Engineering (MSME) / The automotive industry is on the verge of groundbreaking transformations as a result of electrification and autonomous driving. Electrified autonomous car of the future is sustainable, energy-efficient, more convenient, and safer. In addition to the advantages of electrification and autonomous driving individually, the intersection and interaction of these mainstreams provide new opportunities for further improvements on the vehicles. Autonomous cars generate an unprecedented amount of real-time data due to excessive use of perception sensors and processing units. This thesis considers the case of an autonomous hybrid electric vehicle and presents the novel idea of autonomous-specific energy management strategy. Specifically, this thesis is a proof-of-concept, a trial to exploit the motion planning data for a self-driving car to improve the fuel economy of the hybrid electric power unit by adopting a more efficient energy management strategy. With the ever-increasing number of autonomous hybrid electric vehicles, particularly in the self-driving fleets, the presented method shows an extremely promising potential to reduce the fuel consumption of these vehicles.

The main body of this thesis consists of six appended papers. In the  first two, different  cooperative surveillance problems are considered. The second two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.In Papers A and B,  a combinatorial optimization based framework to cooperative surveillance missions using multiple Unmanned Ground Vehicles (UGVs) is proposed. In particular, Paper A  considers the the Minimum Time UGV Surveillance Problem (MTUSP) while Paper B treats the Connectivity Constrained UGV Surveillance Problem (CUSP). The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from  a point on a waypoint-path and such that the time for executing the search in parallel is minimized.  The connectivity constrained formulation  extends the MTUSP by additionally requiring the induced information graph to be  kept recurrently connected  at the time instants when the UGVs  perform the surveillance mission.  In these two papers, the NP-hardness of  both these problems are shown and decomposition techniques are proposed that allow us to find an approximative solution efficiently in an algorithmic manner.Paper C addresses the problem of designing a real time, high performance trajectory planner for an aerial vehicle that uses information about terrain and enemy threats, to fly low and avoid radar exposure on the way to a given target. The high-level framework augments Receding Horizon Control (RHC) with a graph based terminal cost that captures the global characteristics of the environment.  An important issue with RHC is to make sure that the greedy, short term optimization does not lead to long term problems, which in our case boils down to two things: not getting into situations where a collision is unavoidable, and making sure that the destination is actually reached. Hence, the main contribution of this paper is to present a trajectory planner with provable safety and task completion properties. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In Paper D, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for  online  trajectory optimization are illustrated by a missile guidance example.In Paper E, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotic systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a  unicycle robot model, equipped with a set of range-measuring sensors. Finally, in Paper F, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented  by  a proof  that the region of contraction is infinitely thin. Moreover, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature. / QC 20100622 / TAIS, AURES

<p>The main body of this thesis consists of four appended papers. The first two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.</p><p>The first paper addresses the problem of designing a real time, high performance trajectory planner for aerial vehicles. The main contribution is two-fold. Firstly, by augmenting a novel safety maneuver at the end of the planned trajectory, this paper extends previous results by having provable safety properties in a 3D setting. Secondly, assuming initial feasibility, the planning method is shown to have finite time task completion. Moreover, in the second part of the paper, the problem of simultaneous arrival of multiple aerial vehicles is considered. By using a time-scale separation principle, one is able to adopt standard Laplacian control to this consensus problem, which is neither unconstrained, nor first order.</p><p>Direct methods for trajectory optimization are traditionally based on<i> a</i> <i>priori </i>temporal discretization and collocation methods. In the second paper, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for online trajectory optimization are illustrated by a missile guidance example.</p><p>In the third paper, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotics systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors.</p><p>Finally, in the fourth paper, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer recently proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contraction is infinitely thin. However, assuming <i>a</i> <i>priori </i>bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature.</p>

The subject of this diploma thesis is the design of a newly built mixed-use building in Tišnov, as well as elaboration a part of the project documentation for realization of the building construction. The designed building is a multifunctional building, which has the task of providing several functions. The building is situated in the South Moravian Region in the northern part of the village Tišnov, which is located about 30 kilometers away from the city of Brno. Recently, in this area new family houses and apartment buildings have been built. The building is designed as five above-ground storey, partially basement incl. a separate underground car park. The first floor serves mainly for commercial use, ie. for the provision of services and for the sale of goods. There is a coffee shop, a houseware store, hairdressers, bakers, butchers, or a gym. On the first floor there is also the main entrance to the building, and through there is further access to the upper or lower floors of the building. In the basement there is a technical background of the building and access to the underground parking. The second floor serves as office space for multipurpose use. There are apartments on the third, fourth and fifth floor, with some apartments on the 4th floor being designed as two-level maisonettes. The architectural design is based on the concept of straight lines and sharp edges, which also presents a flat roof roofing solution and receding storey with terraces. The building is detached, situated in a relatively flat terrain. All entrances to the building are designed as barrier-free. The white-blue color of the building facade alternates with the use of gray stone cladding. The roofing of the mixed-use building is solved on two levels by a single-layer extensive vegetation flat roof.

The main body of this thesis consists of four appended papers. The first two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively. The first paper addresses the problem of designing a real time, high performance trajectory planner for aerial vehicles. The main contribution is two-fold. Firstly, by augmenting a novel safety maneuver at the end of the planned trajectory, this paper extends previous results by having provable safety properties in a 3D setting. Secondly, assuming initial feasibility, the planning method is shown to have finite time task completion. Moreover, in the second part of the paper, the problem of simultaneous arrival of multiple aerial vehicles is considered. By using a time-scale separation principle, one is able to adopt standard Laplacian control to this consensus problem, which is neither unconstrained, nor first order. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In the second paper, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for online trajectory optimization are illustrated by a missile guidance example. In the third paper, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotics systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors. Finally, in the fourth paper, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer recently proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contraction is infinitely thin. However, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature. / QC 20101108