Autonomous system (mathematics)

About: Autonomous system (mathematics) is a research topic. Over the lifetime, 1648 publications have been published within this topic receiving 38373 citations.

A Semi-Autonomous Reactive Control Architecture

Abstract: This paper presents a novel intelligent control architecture for semi-autonomous systems. A semi-autonomous system is defined here as that autonomous system (machine) which interacts intelligently with a human user (collaborator) who might command, modify, or override its behavior. This work has been motivated by the need for a control architecture that can interact with human users of different perceptual and cognitive capabilities. A dynamic arbitration layer forms the core of the proposed architecture. Accordingly, the architecture evolves around three main variables: degree of autonomy to reflect the user's capabilities, user's level of confidence in commanding the machine, and strength of conflict between the user's command and the machine's autonomous command. The analogy between this architecture and horseback riding is presented and finally a demonstrative application example of a robotic wheelchair is given.

Collaborative Mapping with IoE-based Heterogeneous Vehicles for Enhanced Situational Awareness

Abstract: The development of autonomous vehicles or advanced driving assistance platforms has had a great leap forward to get closer to human daily life over the last decade. Nevertheless, it is still challenging to achieve an efficient and fully autonomous vehicle or driving assistance platform due to many strict requirements and complex situations or unknown environments. One of the main remaining challenges is a robust situation awareness in autonomous vehicles when the environment is unknoen. An autonomous system with a poor situation awareness due to low quantity or quality of data may directly or indirectly cause serious consequences. For instance, a person’s life might be at risk due to a delay caused by a long or incorrect path planning of an autonomous ambulance. Internet of Everything (IoE) is currently becoming a prominent technology for many applications such as automation. In this paper, we propose an IoE-based architecture consisting of a heterogeneous team of cars and drones for enhancing situational awareness in autonomous cars, especially when dealing with critical cases of natural disasters. In particular, we show how an autonomous car can plan in advance the possible paths to a given destination, and send orders to other vehicles. These, in turn, perform terrain reconnaissance for avoiding obstacles and dealing with difficult situations. Together with a map merging algorithm deployed into the team autonomous vehicles, the proposed architecture can help to save traveling distance and time significantly in case of complex scenarios.

Towards Modeling, Specifying and Deploying Policies in Autonomous and Autonomic Systems Using an AOSE Methodology

Abstract: Autonomic Computing (AC), self-management based on high level guidance from humans, is increasingly gaining momentum as the way forward in designing reliable systems that hide complexity and conquer IT management costs. Effectively, AC may be viewed as Policy-Based Self- Management. We look at ways to achieve this, and in particular focus on Agent-Oriented Software Engineering. We propose utilizing an AOSE methodology for specifying autonomic and autonomous properties of the system independently, and later, by means of composition of these specifications, to construct a specification for the policy and its subsequent deployment.

Optimization of a PV-wind-diesel system using a hybrid genetic algorithm

Abstract: Sizing the physical components, choosing proper brands, setting the optimal operation parameters, and the computation time are crucial issues when designing a diesel-hybrid renewable energy system. In this paper, a variant of one of the conventional methods used for designing and configuring these systems is proposed. This variant employs a hybrid genetic algorithm resulting in a time-efficient searching method. This method was applied in the design of an autonomous system that supplies two of the different kinds of loads typically encountered in Japan. The predicted costs were feasible and encouraging for more investment in this field of power.

User Modelling for Principled Sliding Autonomy in Human-Robot Teams

Abstract: The complexity of heterogeneous robotic teams and the domains in which they are deployed is fast outstripping the ability of autonomous control software to handle the myriad failure modes inherent in such systems. As a result, remote human operators are being brought into the teams as equal members via sliding autonomy to increase the robustness and effectiveness of such teams. A principled approach to deciding when to request help from the human will benefit such systems by allowing them to efficiently make use of the human partner. We have developed a cost-benefit analysis framework and models of both autonomous system and user in order to enable such principled decisions. In addition, we have conducted user experiments to determine the proper form for the learning curve component of the human’s model. The resulting automated analysis is able to predict the performance of both the autonomous system and the human in order to assign responsibility for tasks to one or the other.