A modular approach for the design of the Alicia3 climbing robot for industrial inspection
01 Apr 2004-Industrial Robot-an International Journal (Emerald Group Publishing Limited)-Vol. 31, Iss: 2, pp 148-158
TL;DR: The Alicia3 robot, which is based on the Alicia II module, aims to inspect non‐porous vertical walls like those of aboveground petrochemical tanks, with a wide range of surface materials and cleanliness levels, and pneumatic‐like adhesion has been selected for the system.
Abstract: The system proposed in this paper is the Alicia3 robot, which is based on the Alicia II module. Its aim is to inspect non‐porous vertical walls like those of aboveground petrochemical tanks, with a wide range of surface materials and cleanliness levels. To meet this aim, pneumatic‐like adhesion has been selected for the system. The system is also required to move over the surface at a suitable speed, to pass over obstacles and to have a suitable payload to carry mission‐specific instrumentation. The robot design mainly aimed at finding a solution with a high degree of modularity, so that it can easily be disassembled for maintenance purposes and to replace consumable parts such as the wheels and the sealing, making its design easier. Some onboard control algorithms have also been introduced to increase system reliability and reduce energy consumption.
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TL;DR: A classification of climbing robots and proper examples with a brief outline are presented with considerations of the locomotive and adhesion mechanisms.
Abstract: Climbing robots are robotic systems to move over 2D or complex 3D environments such as walls, ceilings, roofs, and geometric structures and to conduct various tasks. They will not only replace human workers for carrying out risky tasks in hazardous environments, but also increase operational efficiency by eliminating the costly erection of scaffolding and staffing costs. Climbing robots have special characteristics and the ability to adhere to different types of 2D or 3D surfaces, move around, and carry appropriate tools and sensors to work, while self-sustaining their bodies. Therefore, the most significant criterion for designing a climbing robot is to equip it with an appropriate locomotive and adhesion mechanism for adapting to the given environmental requirements. In this paper, a classification of climbing robots and proper examples with a brief outline are presented with considerations of the locomotive and adhesion mechanisms. Also, a list of climbing robots is provided with respect to fields of application that range from cleaning tasks in the construction industry to human care systems in the biomedical service industry.
208 citations
TL;DR: The aim of this project is to develop a system that can be adopted in a variety of applications, such as maintenance, building, inspection, and safety in the process and construction industries.
Abstract: The system proposed in this article is the Alicia/sup 3/ climbing robot. The aim of this project is to develop a system that can be adopted in a variety of applications, such as maintenance, building, inspection, and safety in the process and construction industries. The system could be adopted in many places where direct access by a human operator is very expensive because of the need for scaffolding or is very dangerous due to the presence of a hostile environment.
119 citations
TL;DR: Omniclimber, a new climbing robot with high maneuverability for inspection of ferromagnetic flat and convex human made structures and adaptability to various structures with different curvatures and materials is introduced.
111 citations
Cites background from "A modular approach for the design o..."
...For holding a robot attached to a smooth surface, the mainly used systems are: suction cups [1], [2], [3], [4], attraction force generated by propeller (negative pressure) [5], [6] or magnets [7], [8], [9], [10]....
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TL;DR: The designs of climbing robots for glass‐wall cleaning can avoid workers presence in a hazardous environment and realize an automatic cleaning, furthermore reduce operation costs and improve the technological level and productivity of the service industry in the building maintenance.
Abstract: – This paper presents the design of climbing robots for glass‐wall cleaning., – A systemic analysis of the basic functions of a glass‐wall cleaning system is given based on the research of working targets. Then the constraints for designing a glass‐wall cleaning robot are discussed. The driving method, the attachment principle, mechanical structure and unique aspects of three pneumatic robots named Sky Cleaners follow. In the end a summary of the main special features is given. All three climbing robots are tested on site., – Our groups spent several years in designing and developing a series of robots named Sky Cleaners which are totally actuated by pneumatic cylinders and sucked to the glass walls with vacuum grippers in mid‐air. It was found that they can meet the requirements of glass‐wall cleaning., – The air source, cleaning liquid and control signals should be provided by the supporting vehicle stationed on the ground. Even if the robots are intelligent, the suitable working height is below 50 m because the weight of the hoses has to be taken into account when the robots work in mid‐air., – The cleaning robotic systems can avoid workers presence in a hazardous environment and realize an automatic cleaning, furthermore reduce operation costs and improve the technological level and productivity of the service industry in the building maintenance., – Sky Cleaner robots can move and do cleaning on the plane glass wall or the special curve wall with a small angle between the glasses. The first two prototypes are mainly used for research and the last one is a real product designing for cleaning the glass surface of Shanghai Science and Technology Museum.
71 citations
Cites background from "A modular approach for the design o..."
...Reliable non-destructive evaluation and diagnosis in hazardous environments such as the nuclear industry, the chemical industry and the power generation industry ( Long and Muscato, 2004...
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01 Aug 2008
56 citations
References
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TL;DR: It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems and the models introduced are practically feasible.
Abstract: It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described. >
7,692 citations
TL;DR: It is shown that a neural network can learn of its own accord to control a nonlinear dynamic system and should be applicable to a wide variety of nonlinear control problems.
Abstract: It is shown that a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper', a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems. >
811 citations
TL;DR: A case is made in this paper that such approximate input-output models warrant a detailed study in their own right in view of their mathematical tractability as well as their success in simulation studies.
Abstract: The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.
475 citations
"A modular approach for the design o..." refers methods in this paper
...This controller was simulated in various configurations ( Narendra and Mukhopadhyay, 1997...
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TL;DR: In this paper, an algorithm for identifying NARMAX models based on radial basis functions from noise-corrupted data is presented. But this algorithm is not suitable for the analysis of a wide class of discrete-time nonlinear systems.
Abstract: A wide class of discrete-time non-linear systems can be represented by the nonlinear autoregressive moving average (NARMAX) model with exogenous inputs. This paper develops a practical algorithm for identifying NARMAX models based on radial basis functions from noise-corrupted data. The algorithm consists of an iterative orthogonal-forward-regression routine coupled with model validity tests. The orthogonal-forward-regression routine selects parsimonious radial-basisTunc-tion models, while the model validity tests measure the quality of fit. The modelling of a liquid level system and an automotive diesel engine are included to demonstrate the effectiveness of the identification procedure.
312 citations
"A modular approach for the design o..." refers methods in this paper
...Moreover, the system has to be considered as a non-linear one to improve simulator accuracy, so a nonlinear auto regressive with exogenous inputs (NARX) model was used, where the non-linear function is interpolated with an artificial neural network (ANN) ( Chen et al. , 1990...
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TL;DR: In this article, a climbing robot with eight suction cups was proposed to change its climbing direction to carry an ultrasonic probe or other non-destructive tests (NDT) equipment to evaluate the thickness and integrity of the metal in the inspection of storage tanks.
157 citations