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In this paper we present a trajectory generation scheme for approximate way point tracking for a nonholonomic differential wheeled mobile robot. The generated trajectories are guaranteed to satisfy the nonholonomic dynamics and minimizes the jerk of the center of mass motion of the robot. Minimizing jerk is desirable to ensure the smoothness of the trajectories and is often necessary to ensure physical...
This paper presents a method to incorporate measurement of local magnetic field anomalies into the SLAM (Simultaneous Localization And Mapping) algorithm. One of the key problems of SLAM is loop closure, which means to map the same place into the same location on the generated map when the place is revisited by the robot. It is particularly important for large area map consistency. Steel structures,...
It is necessary to determine the robot's pose to localize a mobile robot in a known environment. If there is no information about the initial location, we are talking about global localization. In our previous work we solved this problem in a two-dimensional environment with an algorithm known as Evolutive Localization Filter (ELF). Based on evolutionary computation concepts, the proposed algorithm...
Global localization methods deal with the estimation of a mobile robot's pose assuming no prior state information about it and a complete a priori knowledge of the environment where the mobile robot is going to be localized. Most existent algorithms are based on the minimization of a L2-norm loss function. However, the use of a L1-norm offers some alternative advantages. The present work explores...
This paper presents the application to nonholonomic mobile robot path planning of our Voronoi fast marching (VFM) and FM2 methods, which represents our current progress on the design and analysis of these algorithms. The VFM and FM2 methods use the propagation of a wave (fast marching) operating on the world model, to determine a motion plan over a slowness map (similar to the refraction index in...
This paper presents a new method to improve the trajectories based in the Voronoi fast marching method (VFM). It can be used to improve the smoothness and the length of the trajectories calculated with probabilistic methods with bad quality trajectories such as RRT or PRM. This way, it is possible to get the good properties of the RRT method as the fact that it can work in many dimensions with the...
A new solution to the simultaneous localization and modelling problem is presented. It is based on the stochastic search of solutions in the state space to the global localization problem by means of a differential evolution algorithm. A non linear evolutive filter, called evolutive localization filter (ELF), searches stochastically along the state space for the best robot pose estimate. The proposed...
The Extended Voronoi Transform and the Fast Marching Method combination provide potential maps for robot navigation in previously unexplored dynamic environments. The Logarithm of the Extended Voronoi Transform imitates the repulsive electric potential from walls and obstacles. The method proposed, called Voronoi Fast Marching method, uses a Fast Marching technique on the Extended Voronoi Transform...
Mobile robot global localization aims to determine the robot's pose in a known environment in absence of initial robot's pose information. This article presents an evolutive localization algorithm known as Evolutive Localization filter (ELF). Based on evolutionary computation concepts, the proposed algorithm search stochastically along the state space the best robot's pose estimate. The set of pose...
A new solution to the Simultaneous Localization and Modelling problem is presented. It is based on the stochastic search of solutions in the state space to the global localization problem by means of a differential evolution algorithm. A non linear evolutive filter, called Evolutive Localization Filter (ELF), searches stochastically along the state space for the best robot pose estimate. The proposed...
Path planning for autonomous robots is an essential capacity for these systems. One class of path planning algorithms use potential fields. However, some problems associated with these algorithms include (1) Trapping due to local minima, (2) No passage between closely spaced obstacles, and (3) Limit cycles. This paper presents a potential-field-based algorithm that does not exhibit the mentioned problems...
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