Carlos Cerrada

Load adaptive control of single-link flexible arms based on a new modeling technique

A new method for controlling single-link flexible manipulators is proposed. The objective is to control the tip position of a flexible manipulator in the presence of changes in its payload. Particularly, a new adaptive control system has been designed. The proposed control system requires calculating only one parameter, the tip load, instead of all the transfer functions as in conventional adaptive control methods. The tip load identification algorithm is based on the equivalence existing between a manipulator with payload and a manipulator submitted to the action of external forces. Moreover, this equivalence provides a new technique for modeling these systems which simplifies the methods usually applied. This results in a simple control law that needs minimal computing effort and, thus, can be used for real-time control of flexible arms.

Automatic Method for Building Indoor Boundary Models from Dense Point Clouds Collected by Laser Scanners

In this paper we present a method that automatically yields Boundary Representation Models (B-rep) for indoors after processing dense point clouds collected by laser scanners from key locations through an existing facility. Our objective is particularly focused on providing single models which contain the shape, location and relationship of primitive structural elements of inhabited scenarios such as walls, ceilings and floors. We propose a discretization of the space in order to accurately segment the 3D data and generate complete B-rep models of indoors in which faces, edges and vertices are coherently connected. The approach has been tested in real scenarios with data coming from laser scanners yielding promising results. We have deeply evaluated the results by analyzing how reliably these elements can be detected and how accurately they are modeled.

Automatic Construction of 3D Basic-Semantic Models of Inhabited Interiors Using Laser Scanners and RFID Sensors

This paper is focused on the automatic construction of 3D basic-semantic models of inhabited interiors using laser scanners with the help of RFID technologies. This is an innovative approach, in whose field scarce publications exist. The general strategy consists of carrying out a selective and sequential segmentation from the cloud of points by means of different algorithms which depend on the information that the RFID tags provide. The identification of basic elements of the scene, such as walls, floor, ceiling, windows, doors, tables, chairs and cabinets, and the positioning of their corresponding models can then be calculated. The fusion of both technologies thus allows a simplified 3D semantic indoor model to be obtained. This method has been tested in real scenes under difficult clutter and occlusion conditions, and has yielded promising results.

Evolution of RFID Applications in Construction: A Literature Review.

Radio frequency identification (RFID) technology has been widely used in the field of construction during the last two decades. Basically, RFID facilitates the control on a wide variety of processes in different stages of the lifecycle of a building, from its conception to its inhabitance. The main objective of this paper is to present a review of RFID applications in the construction industry, pointing out the existing developments, limitations and gaps. The paper presents the establishment of the RFID technology in four main stages of the lifecycle of a facility: planning and design, construction and commission and operation and maintenance. Concerning this last stage, an RFID application aiming to facilitate the identification of pieces of furniture in scanned inhabited environments is presented. Conclusions and future advances are presented at the end of the paper.

Modeling Wave Set

In this paper we deal with the problem of constructing geometric models from 3D data points from the surface of real objects. The model generated by our system handles a complete mesh of the object surface obtained by deformation of an initial mesh. Basic topologies, such as three or six connectivity, provide a local and poor characterization in the representation mesh. Therefore, we have introduced a new topological organization called modeling wave set (MWS) where an n-connectivity relationship is established. With the MWS, an object is simultaneously modeled in n subspaces of features, corresponding to n different viewing directions of the object. The use of MWS allows for new solutions to typical computer vision problems, such as recognition and positioning, to be found. Our paper shows this topology and the way it has been tested in detail. Partial modeling based on MWS is a promising research line along which we have started to work and to obtain satisfactory results.

Improved Method for Object Recognition in Complex Scenes by Fusioning 3-D Information and RFID Technology

This work analyzes a new method for object recognition in complex scenes combining vision-based techniques applied to the 3-D data obtained using range sensors and object identification coming from radio frequency tags (radio frequency identification (RFID) technology). Three-dimensional vision-based algorithms for object recognition have many restrictions in practical applications, i.e., uncertainty, incapability for real-time tasks, etc., but they work well for pose determination once the object is recognized. On the other hand, RFID technology allows us to detect the presence of specific objects in a scene, but it cannot provide their localization, at least not with the accuracy required in applications such as ours. In this paper, we present a new and powerful recognition method obtained by fusing both techniques. The phases of the method are described, and abundant experimentation results are included. An in-depth performance analysis has been carried out to demonstrate the recognition improvements achieved by the algorithm when RFID assistance is considered. It helps to confirm the robustness of this fusion approach and prove its effectiveness. A final discussion is included, concerning what should be the most adequate size of the object database for optimal algorithm exploitation.

A method to design multirate controllers for plants sampled at a low rate

Classical discrete control systems allow control of the output of a plant at sampling instants. If control of the output between sampling instants is required, a multirate controller can be used. An analytical procedure is developed that allows feedforward control of the output at multirate instants and feedback control at sampling instants. The method proposed is a practical approach to the model-matching problem and takes into account the intersampling dynamics of the system. >

Global shape invariants: a solution for 3D free-form object discrimination/identification problem

Abstract A method for solving the 3D object recognition problem is described in this paper. The method uses a new set of global features as discriminant parameters. The general purpose of our approach is to achieve simplicity, speed and efficiency by using global invariants. For this, two new global parameters are introduced, which are invariant to rotation, translation and scaling: canonical length (CL), which provides an indirect measurement of object surface and weighted principal directions (WPDs) corresponding to the meaningful normal directions of the object surface. Abundant experimentation has been conducted with a real world system in order to validate the method.

A New Control Scheme of Single-link Flexible Manipulators Robust to Payload Changes

A new scheme is presented in this paper to control single-link flexiblemanipulators. The objective is to control the tip position of the flexiblearm in the presence of joint friction and payload changes. The controlscheme is based on two nested loops: an inner feedback loop to control themotor position which is robust to joint friction, and an outer loop tocontrol the tip position which is robust to payload changes. This outer loopis composed of a feedforward term and a feedback term. This results in asimple control law that needs minimal computing effort and, thus, can beused for real time control of flexible arms. The proposed method is generalin the sense that it can be applied to very different arm structures anddiverse sensor systems configurations. Results corresponding to twodifferent arm setups are presented.

Detection, Modeling, and Classification of Moldings for Automated Reverse Engineering of Buildings from 3D Data

Laser scanner data is increasingly being used for the detailed reverse engineering of buildings. This process is currently primarily manual, but recent research has shown that basic structures, such as walls, ceilings, floors, doorways, and windows, can be detected and modeled automatically. Building on this previous research, we focus on the modeling of those linear moldings that typically surround doorways, windows, and divide ceilings from walls and walls from floors. These structures may be secondary and merely ornamental, but many projects nevertheless require that they be modeled. Moldings can be difficult to model manually owing to missing data caused by occlusions or to the ambiguity caused by low data density. Our molding modeling approach consists of two steps: 1) estimating the path of the molding; and 2) estimating the shape of the molding profile. In the first step, we iteratively update the molding’s line of extrusion by optimizing the similarity of cross-sections sampled along the path, thereby compensating for imperfections in the initial orientation estimate. In the second step, a unified profile is extracted using data from the entire length of the molding, which allows for partial missing data from occlusions. The profile is then characterized by a specific shape descriptor. Finally, a KNN algorithm classifies the molding into a database which has been constructed with profiles originating from various molding manufacturers. We demonstrate the method using real 3D laser scanner data of various types of moldings, both simple and complex.