Abstract
The continued development of mobile robots (MR) must be accompanied by an increase in robotics’ safety measures. Not only must MR be capable of detecting and diagnosing faults, they should also be capable of understanding when the dangers of a mission, to themselves and the surrounding environment, warrant the abandonment of their endeavors. Analysis of fault detection and diagnosis techniques helps shed light on the challenges of the robotic field, while also showing a lack of research in autonomous decision-making tools. This paper proposes a new skill-based architecture for mobile robots, together with a novel risk assessment and decision-making model to overcome the difficulties currently felt in autonomous robot design.
Highlights
Robotics can be seen as a scientific art, a branch of engineering that aims to develop automated tools that can mimic human ability to manipulate the environment
Research on fault diagnosis and fault tolerance directed at mobile robots is a recent risk assessment and decision-making models
Despite the problems concerning model-based methods, in recent years, it remained an important base for works in the field, including the development of a technique that aimed to overcome a deficiency found in most approaches, as most only consider the occurrence of isolated faults and fail to address simultaneous faults or, in alternative, require sensor redundancy to detect these situations
Summary
Robotics can be seen as a scientific art, a branch of engineering that aims to develop automated tools that can mimic human ability to manipulate the environment Such systems, to achieve this goal, require various components, which can be divided as: sensor, power source, actuators, controllers and a physical structure—a body that can house all these parts [1], akin to how the human body houses various organs, bones and muscles to allow the perceiving and manipulation of their surroundings. One possible solution is the use of a safety monitoring system, capable of defining when, given a mission, the robot has the necessary conditions to follow it through or when it should cancel the operation and, for example, return to base for repairs For this decision to be correct though, it can’t be taken blindly.
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