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The interest in the development of climbing robots has grown rapidly in the last years. Climbing
robots are useful devices that can be adopted in a variety of applications, such as maintenance
and inspection in the process and construction industries. These systems are mainly
adopted in places where direct access by a human operator is very expensive, because of the
need for scaffolding, or very dangerous, due to the presence of an hostile environment. The
main motivations are to increase the operation efficiency, by eliminating the costly assembly
of scaffolding, or to protect human health and safety in hazardous tasks. Several climbing
robots have already been developed, and other are under development, for applications ranging
from cleaning to inspection of difficult to reach constructions.
A wall climbing robot should not only be light, but also have large payload, so that it may
reduce excessive adhesion forces and carry instrumentations during navigation. These machines
should be capable of travelling over different types of surfaces, with different inclinations,
such as floors, walls, or ceilings, and to walk between such surfaces (Elliot et al. (2006);
Sattar et al. (2002)). Furthermore, they should be able of adapting and reconfiguring for various
environment conditions and to be self-contained.
Up to now, considerable research was devoted to these machines and various types of experimental
models were already proposed (according to Chen et al. (2006), over 200 prototypes
aimed at such applications had been developed in the world by the year 2006). However,
we have to notice that the application of climbing robots is still limited. Apart from a couple
successful industrialized products, most are only prototypes and few of them can be found
in common use due to unsatisfactory performance in on-site tests (regarding aspects such as
their speed, cost and reliability). Chen et al. (2006) present the main design problems affecting
the system performance of climbing robots and also suggest solutions to these problems.
The major two issues in the design of wall climbing robots are their locomotion and adhesion
methods.
With respect to the locomotion type, four types are often considered: the crawler, the wheeled,
the legged and the propulsion robots. Although the crawler type is able to move relatively
faster, it is not adequate to be applied in rough environments. On the other hand, the legged
type easily copes with obstacles found in the environment, whereas generally its speed is
lower and requires complex control systems.
Regarding the adhesion to the surface, the robots should be able to produce a secure gripping
force using a light-weight mechanism. The adhesion method is generally classified into four groups: suction force, magnetic, gripping to the surface and thrust force type. Nevertheless,
recently new methods for assuring the adhesion, based in biological findings, were proposed.
The vacuum type principle is light and easy to control though it presents the problem of
supplying compressed air. An alternative, with costs in terms of weight, is the adoption of
a vacuum pump. The magnetic type principle implies heavy actuators and is used only for
ferromagnetic surfaces. The thrust force type robots make use of the forces developed by
thrusters to adhere to the surfaces, but are used in very restricted and specific applications.
Bearing these facts in mind, this chapter presents a survey of different applications and technologies
adopted for the implementation of climbing robots locomotion and adhesion to surfaces,
focusing on the new technologies that are recently being developed to fulfill these objectives.
The chapter is organized as follows. Section two presents several applications of
climbing robots. Sections three and four present the main locomotion principles, and the
main "conventional" technologies for adhering to surfaces, respectively. Section five describes
recent biological inspired technologies for robot adhesion to surfaces. Section six introduces
several new architectures for climbing robots. Finally, section seven outlines the main conclusions.
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InTech