Novel solutions for Global Urban Localization

Koku, Ahmet Buğra
Dölen, Melik
In this study, novel solutions to Global Urban Localization problem is proposed and examined rigorously. Classical approaches including Particle Filter, mixture of Gaussians, as well as novel solutions like Viterbi Algorithm and differential evolution are evaluated. The contribution of this paper is twofold: The Viterbi algorithm is extended by exploiting the structure of the problem at hand that is the states are partially connected temporally. Differential evolution is modified by taking into account the covariance matrix of states. Thus states encoded in genes are only allowed to interact locally within the region described by covariance matrix. This prevents the differential evolution from getting trapped into false maxima in the early stages of optimization. Finally, it is demonstrated with extensive experiments that solution of Global Urban Localization problem is possible.


Free gait generation with reinforcement learning for a six-legged robot
Erden, Mustafa Suphi; Leblebicioğlu, Mehmet Kemal (Elsevier BV, 2008-03-31)
In this paper the problem of free gait generation and adaptability with reinforcement learning are addressed for a six-legged robot. Using the developed free gait generation algorithm the robot maintains to generate stable gaits according to the commanded velocity. The reinforcement learning scheme incorporated into the free gait generation makes the robot choose more stable states and develop a continuous walking pattern with a larger average stability margin. While walking in normal conditions with no ext...
Analysis of single Gaussian approximation of Gaussian mixtures in Bayesian filtering applied to mixed multiple-model estimation
Orguner, Umut (Informa UK Limited, 2007-01-01)
This paper examines the effect of the moment-matched single Gaussian approximation, which is made in various multiple-model filtering applications to approximate a Gaussian mixture, on the Bayesian filter performance. The estimation error caused by the approximation is analysed for both the prediction and the measurement updates of a Bayesian filter. An approximate formula is found for the covariance of the error caused by the approximation for a general Gaussian mixture with arbitrary components. The calcu...
A unifying grid approach for solving potential flows applicable to structured and unstructured grid configurations
Cete, A. Ruhsen; Yuekselen, M. Adil; Kaynak, Uenver (Elsevier BV, 2008-01-01)
In this study, an efficient numerical method is proposed for unifying the structured and unstructured grid approaches for solving the potential flows. The new method, named as the "alternating cell directions implicit - ACDI", solves for the structured and unstructured grid configurations equally well. The new method in effect applies a line implicit method similar to the Line Gauss Seidel scheme for complex unstructured grids including mixed type quadrilateral and triangle cells. To this end, designated al...
An improved method for inference of piecewise linear systems by detecting jumps using derivative estimation
Selcuk, A. M.; Öktem, Hüseyin Avni (Elsevier BV, 2009-08-01)
Inference of dynamical systems using piecewise linear models is a promising active research area. Most of the investigations in this field have been stimulated by the research in functional genomics. In this article we study the inference problem in piecewise linear systems. We propose first identifying the state transitions by detecting the jumps of the derivative estimates, then finding the guard conditions of the state transitions (thresholds) from the values of the state variables at the state transitio...
Vision based obstacle detection and avoidance using low level image features
Senlet, Turgay; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2006)
This study proposes a new method for obstacle detection and avoidance using low-level MPEG-7 visual descriptors. The method includes training a neural network with a subset of MPEG-7 visual descriptors extracted from outdoor scenes. The trained neural network is then used to estimate the obstacle presence in real outdoor videos and to perform obstacle avoidance. In our proposed method, obstacle avoidance solely depends on the estimated obstacle presence data. In this study, backpropagation algorithm on mult...
Citation Formats
C. U. DOĞRUER, A. B. Koku, and M. Dölen, “Novel solutions for Global Urban Localization,” ROBOTICS AND AUTONOMOUS SYSTEMS, pp. 634–647, 2010, Accessed: 00, 2020. [Online]. Available: