Negotiating the Probabilistic Satisfaction of Temporal Logic Motion Specifications

We propose a human-supervised control synthesis method for a stochastic Dubins vehicle such that the probability of satisfying a specification given as a formula in a fragment of Probabilistic Computational Tree Logic (PCTL) over a set of environmental properties is maximized. Under some mild assumptions, we construct a finite approximation for the motion of the vehicle in the form of a tree-structured Markov Decision Process (MDP). We introduce an efficient algorithm, which exploits the tree structure of the MDP, for synthesizing a control policy that maximizes the probability of satisfaction. For the proposed PCTL fragment, we define the specification update rules that guarantee the increase (or decrease) of the satisfaction probability. We introduce an incremental algorithm for synthesizing an updated MDP control policy that reuses the initial solution. The initial specification can be updated, using the rules, until the supervisor is satisfied with both the updated specification and the corresponding satisfaction probability. We propose an offline and an online application of this method.Comment: 9 pages, 4 figures; The results in this paper were presented without proofs in IEEE/RSJ International Conference on Intelligent Robots and Systems November 3-7, 2013 at Tokyo Big Sight, Japa

Vehicle control from temporal logic specifications with probabilistic satisfaction guarantees

Thesis (Ph.D.)--Boston UniversityTemporal logics, such as Linear Temporal Logic (LTL) and Computation Tree Logic (CTL), have become increasingly popular for specifying complex mission specifications in motion planning and control synthesis problems. This dissertation proposes and evaluates methods and algorithms for synthesizing control strategies for different vehicle models from temporal logic specifications. Complex vehicle models that involve systems of differential equations evolving over continuous domains are considered. The goal is to synthesize control strategies that maximize the probability that the behavior of the system, in the presence of sensing and actuation noise, satisfies a given temporal logic specification. The first part of this dissertation proposes an approach for designing a vehicle control strategy that maximizes the probability of accomplishing a motion specification given as a Probabilistic CTL (PCTL) formula. Two scenarios are examined. First, a threat-rich environment is considered when the motion of a vehicle in the environment is given as a finite transition system. Second, a noisy Dubins vehicle is considered. For both scenarios, the motion of the vehicle in the environment is modeled as a Markov Decision Process (MDP) and an approach for generating an optimal MDP control policy that maximizes the probability of satisfying the PCTL formula is introduced. The second part of this dissertation introduces a human-supervised control synthesis method for a noisy Dubins vehicle such that the expected time to satisfy a PCTL formula is minimized, while maintaining the satisfaction probability above a given probability threshold. A method for abstracting the motion of the vehicle in the environment in the form of an MDP is presented. An algorithm for synthesizing an optimal MDP control policy is proposed. If the probability threshold cannot be satisfied with the initial specification, the presented framework revises the specifica- tion until the supervisor is satisfied with the revised specification and the satisfaction probability is above the threshold. The third part of this dissertation focuses on the problem of stochastic control of a noisy differential drive mobile robot such that the probability of satisfying a time constrained specification, given as a Bounded LTL (BLTL) formula, is maximized. A method for mapping noisy sensor measurements to an MDP is introduced. Due to the size of the MDP, finding the exact solution is computationally too expensive. Correctness is traded for scalability, and an MDP control synthesis method based on Statistical Model Checking is introduced

Neizrazito analitičko upravljanje mobilnim robotom u nepoznatoj okolini pomoću metode potencijalnih polja

U sklopu ovog diplomskog rada izrađen je program za simulaciju gibanja mobilnog robota u radnom prostoru, od početne pozicije do cilja a da pritom izbjegava prepreke pri čemu se koristi metoda potencijalnih polja te analitičko neizrazito upravljanje. Uz kratki opis povijesnog razvoja mobilnih robota, naznačeni su njihovi osnovni podsustavi te je izvršena sistematizacija mobilnih robota. \Naglasak je na mobilnim robotima u industriji i dan je prikaz osnovnih problema koji se javljaju prilikom upravljanje mobilnim robotima. U radu su iznesene osnove neizrazite logike i metode potencijalnih polja, dva područja na kojima se bazira upravljački zakon. Uz to, objašnjen je kinematički model mobilnog robota te pojedina područja analitičke geometrije ravnine koja se primjenjuju u radu. Računalni program pisan je u Matlabu, a metoda za rješavanje diferencijalnih jednadžbi je funkcija za numeričko rješavanje diferencijalnih jednadžbi ode45, čiji je osnovni princip opisan u radu. Rezultati simulacija prikazuju gibanje mobilnog robota u radnom prostoru između prepreka u pravokutnom koordinatnom sustavu, a uz to dana je ovisnost upravljačkih varijabli o vremenu za svaku simulaciju

Preceptivne varke

Prikaz geometrijskih perceptivnih varki

Probabilistically safe vehicle control in a hostile environment

In this paper we present an approach to control a vehicle in a hostile environment with static obstacles and moving adversaries. The vehicle is required to satisfy a mission objective expressed as a temporal logic specification over a set of properties satisfied at regions of a partitioned environment. We model the movements of adversaries in between regions of the environment as Poisson processes. Furthermore, we assume that the time it takes for the vehicle to traverse in between two facets of each region is exponentially distributed, and we obtain the rate of this exponential distribution from a simulator of the environment. We capture the motion of the vehicle and the vehicle updates of adversaries distributions as a Markov Decision Process. Using tools in Probabilistic Computational Tree Logic, we find a control strategy for the vehicle that maximizes the probability of accomplishing the mission objective. We demonstrate our approach with illustrative case studies

Estimating Minimum Polycrystalline Aggregate Size for Macroscopic Material Homogeneity

ABSTRACT During severe accidents the pressure boundary of reactor coolant system can be subjected to extreme loadings, which might cause failure. Reliable estimation of the extreme deformations can be crucial to determine the consequences of severe accidents. Important drawback of classical continuum mechanics is idealization of inhomogenous microstructure of materials. Classical continuum mechanics therefore cannot predict accurately the differences between measured responses of specimens, which are different in size but geometrical similar (size effect). A numerical approach, which models elastic-plastic behavior on mesoscopic level, is proposed to estimate minimum size of polycrystalline aggregate above which it can be considered macroscopically homogeneous. The main idea is to divide continuum into a set of sub-continua. Analysis of macroscopic element is divided into modeling the random grain structure (using Voronoi tessellation and random orientation of crystal lattice) and calculation of strain/stress field. Finite element method is used to obtain numerical solutions of strain and stress fields. The analysis is limited to 2D models

Neizrazito analitičko upravljanje mobilnim robotom u nepoznatoj okolini pomoću metode potencijalnih polja

U sklopu ovog diplomskog rada izrađen je program za simulaciju gibanja mobilnog robota u radnom prostoru, od početne pozicije do cilja a da pritom izbjegava prepreke pri čemu se koristi metoda potencijalnih polja te analitičko neizrazito upravljanje. Uz kratki opis povijesnog razvoja mobilnih robota, naznačeni su njihovi osnovni podsustavi te je izvršena sistematizacija mobilnih robota. \Naglasak je na mobilnim robotima u industriji i dan je prikaz osnovnih problema koji se javljaju prilikom upravljanje mobilnim robotima. U radu su iznesene osnove neizrazite logike i metode potencijalnih polja, dva područja na kojima se bazira upravljački zakon. Uz to, objašnjen je kinematički model mobilnog robota te pojedina područja analitičke geometrije ravnine koja se primjenjuju u radu. Računalni program pisan je u Matlabu, a metoda za rješavanje diferencijalnih jednadžbi je funkcija za numeričko rješavanje diferencijalnih jednadžbi ode45, čiji je osnovni princip opisan u radu. Rezultati simulacija prikazuju gibanje mobilnog robota u radnom prostoru između prepreka u pravokutnom koordinatnom sustavu, a uz to dana je ovisnost upravljačkih varijabli o vremenu za svaku simulaciju

Neizrazito analitičko upravljanje mobilnim robotom u nepoznatoj okolini pomoću metode potencijalnih polja

U sklopu ovog diplomskog rada izrađen je program za simulaciju gibanja mobilnog robota u radnom prostoru, od početne pozicije do cilja a da pritom izbjegava prepreke pri čemu se koristi metoda potencijalnih polja te analitičko neizrazito upravljanje. Uz kratki opis povijesnog razvoja mobilnih robota, naznačeni su njihovi osnovni podsustavi te je izvršena sistematizacija mobilnih robota. \Naglasak je na mobilnim robotima u industriji i dan je prikaz osnovnih problema koji se javljaju prilikom upravljanje mobilnim robotima. U radu su iznesene osnove neizrazite logike i metode potencijalnih polja, dva područja na kojima se bazira upravljački zakon. Uz to, objašnjen je kinematički model mobilnog robota te pojedina područja analitičke geometrije ravnine koja se primjenjuju u radu. Računalni program pisan je u Matlabu, a metoda za rješavanje diferencijalnih jednadžbi je funkcija za numeričko rješavanje diferencijalnih jednadžbi ode45, čiji je osnovni princip opisan u radu. Rezultati simulacija prikazuju gibanje mobilnog robota u radnom prostoru između prepreka u pravokutnom koordinatnom sustavu, a uz to dana je ovisnost upravljačkih varijabli o vremenu za svaku simulaciju

Modeling Grain Boundary Damage Evolution in As-Measured 3D Microstructure

In recent years we have seen a development of novel experimental techniques that enable one to non-destructively characterize polycrystalline microstructures. These techniques hold significant advantages over approaches like serial sectioning since the specimen is not destroyed in the characterization process. This is of immense value in advancing our understanding of materials and advancing multiscale computational models. In particular, processes at the small length scales like the initiation and early development of grain boundary damage can now be measured more closely while the resulting simulations can now be directly compared to the experimental data. The task is, however, far from being simple as extremely complex geometry needs to be coupled with advance constitutive models for the bulk grain material and the grain boundaries themselves need to be combined. In this work a model, based on a X-ray diffraction contrast tomography data of a stainless steel wire with a diameter of 0.4mm is presented. 3D topology and crystallographic orientation of individual grains are directly transferred into a finite element model. Grain boundary damage initialization and early development is then explored for a number of cases, ranging from isotropic elasticity up to crystal plasticity constitutive laws for the bulk grain material. In all cases the grain boundaries are modeled using the cohesive zone approach. Also, the stability of the simulations and measures aimed at improving it are reported upon.JRC.F.5-Safety of present nuclear reactor