Catálogo de publicaciones - libros

This paper presents a method for planning three-dimensional walking patterns for biped robots in order to obtain stable smooth dynamic motion and also maximum velocity during walking. To determine the rotational trajectory for each actuator, there are some particular key points gained from natural human walking whose value is defined at the beginning, end and some intermediate or specific points of a motion cycle. The constraint equation of the motion between the key points will be then formulated in such a way to be compatible with geometrical constraints. This is first done in sagittal and then developed to lateral plane of motion. In order to reduce frequent switching due to discrete equations which is inevitable using coulomb dry friction law and also to have better similarity with the natural contact, a new contact model for dynamic simulation of foot ground interaction has been developed which makes the cyclic discrete equations continuous and can be better solved with ODE solvers. Finally, the advantages of the trajectory described are illustrated by simulation results.

We have developed an automatic calibration method for a global camera system. Firstly, we show how to define automatically the color maps we use for tracking the robots’ markers. The color maps store the parameters of each important color in a grid superimposed virtually on the field. Secondly, we show that the geometric distortion of the camera can be computed automatically by finding white lines on the field. The necessary geometric correction is adapted iteratively until the white lines in the image fit the white lines in the model. Our method simplifies and speeds up significantly the whole setup process at RoboCup competitions. We will use these techniques in RoboCup 2004.

In order to detect objects using colour information, the mapping from points in colour space to the most likely object must be known. This work proposes an adaptive colour calibration based on the Bayes Theorem and chrominance histograms. Furthermore the object’s shape is considered resulting in a more robust classification. A randomised hough transform is employed for the ball. The lines of the goals and flagposts are extracted by an orthogonal regression. Shape detection corrects over- and undersegmentations of the colour segmentation, thus enabling an update of the chrominance histograms. The entire algorithm, including a segmentation and a recalibration step, is robust enough to be used during a RoboCup game and runs in real-time.

We investigate the application of a Monte Carlo localization filter to the problem of combining local and global observations of a small, off-the-shelf quadruped domestic robot, in a simulated environment, for the purpose of robust tracking and localization. A Sony Aibo ERS-210A robot forms part of this project, with the ultimate aim of providing additional monitoring, human-system interaction and companionship to the occupants.

We present a complete system for obstacle avoidance for a mobile robot. It was used in the RoboCup 2003 obstacle avoidance challenge in the Sony Four Legged League. The system enables the robot to detect unknown obstacles and reliably avoid them while advancing toward a target. It uses monocular vision data with a limited field of view. Obstacles are detected on a level surface of known color(s). A radial model is constructed from the detected obstacles giving the robot a representation of its surroundings that integrates both current and recent vision information. Sectors of the model currently outside the current field of view of the robot are updated using odometry. Ways of using this model to achieve accurate and fast obstacle avoidance in a dynamic environment are presented and evaluated. The system proved highly successful by winning the obstacle avoidance challenge and was also used in the RoboCup championship games.

In this paper we show how a combination of multiple neuromorphic vision sensors can achieve the same higher level visual processing tasks as carried out by a conventional vision system. We process the multiple neuromorphic sensory signals with a standard auto-regression method in order to fuse the sensory signals and to achieve higher level vision processing tasks at a very high update rate. We also argue why this result is of great relevance for the application domain of reactive and lightweight mobile robotics, at the hands of a soccer robot, where the fastest sensory-motor feedback loop is imperative for a successful participation in a RoboCup soccer competition.

In 2004, the playing field size of the small sized league was significantly increased, posing new challenges for all teams. This paper describes extensions to our current video server software (Doraemon) to deal with these new challenges. It shows that a camera with a side view is a workable alternative to the more expensive approach of using multiple cameras. The paper discusses the camera calibration method used in Doraemon as well as an investigation into some common two–dimensional interpolation methods, as well a novel average gradient method. It also proves that (ignoring occluded parts of the playing field) it is possible to construct a realistic top down view of the playing field with a camera that only has a side view of the field.

Multiple cameras have been used to get a view of a large area. In some cases, the cameras are placed so that their views are overlapped to get a more complete view. 3D information of the overlapping areas that are covered with two or three cameras can be obtained by stereo vision methods. By shifting the shutter timings of cameras and using our pseudo stereo vision method, we can output 3D information faster than 30 fps. In this paper, we propose a pseudo stereo vision method using three cameras with different shutter timings. Using three cameras, two types of shutter timings are discussed. In three different shutter timings, 90 points of 3D position for a sec are obtained because the proposed method can output 3D positions at every shutter timing of three cameras. In two different shutter timings, it is possible to calculate the 3D position at 60 fps with better accuracy.

This paper describes a new technique for determining the distance to a planar surface and, at the same time, obtaining a characterization of the surface’s material through the use of conventional, low-cost infrared sensors. The proposed technique is advantageous over previous schemes in that it does not require additional range sensors, such as ultrasound devices, nor a priori knowledge about the materials that can be encountered. Experiments with an all-terrain mobile robot equipped with a ring of infrared sensors are presented.

In this work, a novel search strategy for autonomous search and rescue robots, that is highly suitable for the environments when the aid of human rescuers or search dogs is completely impossible, is proposed. The work area for a robot running this planning strategy can be small voids or possibly dangerous environments. The main goal of the proposed planning strategy is to find victims under very tight time constraints. The exploration strategy is designed to improve the success of the main goal of the robot using specialized sensors when available. The secondary goals of the strategy are avoiding obstacles for preventing further collapses, avoiding cycles in the search, and handling errors. The conducted experiments show that the proposed strategies are complete and promising for the main goal of a SR robot. The number of steps to find the reachable victims is considerably smaller than that of the greedy mapping method.