Service-oriented agent architecture for unmanned air vehicles

Abstract

Unmanned Air Vehicles (UAVs) are performing more and more sophisticated air missions. Remotelypiloted vehicles are becoming less and less costeffective. Alternatively, autonomous UAVs have the potential to operate with greatly reduced overhead costs and level of pilot intervention. The challenge is to develop a system that deploys a team of UAVs that can perform complex tasks reliably and with minimal (remote) pilot intervention. New UAV platforms require high degree of autonomy and a collaborative operation mode in order to minimize the human intervention. This paper proposes an Intelligent Vehicle Control Architecture (IVCA) to enable multiple collaborating air vehicles to autonomously carry out airspace missions. The IVCA is generic in nature but aimed at a case study where UAVs are required to work cooperatively. The architectural foundation to achieve the IVCA lays on the flexibility of service-oriented computing and agent software technology. An ontological database captures the remote pilot skills, platform capabilities and, changes in the environment. The information captured enables reasoning agents to plan missions based on the current situation. This makes it possible to develop an IVCA that is able to dynamically reconfigure and adapt itself in order to deal with changes in the operation environment. This paper also presents architectural details and evaluation scenarios of the IVCA, and future research directions.

Design Principles for Distributed Context Modeling of Autonomous Systems

“…Based on the system's state and the situation at hand, the system independently formulates and selects various actions to accomplish the respective objectives. Autonomous systems possess the capability to perceive and operate in complex and dynamic environments [18,19] and accomplish diverse actions and tasks independently compared to automated systems [20,21]. Autonomy typically requires a system equipped with multisource sensors and software that can process complex tasks, enabling the system to achieve its goals and objectives independently without external communication or with limited communication with the outside world within a specific timeframe, and without the assistance of external intervention.…”

ARCog: An Aerial Robotics Cognitive Architecture

“…This extension can be used in both simulated and real-time environments. Another equivalent improvement was made in the architecture CHREST 8 and employed in the work of Insurralde et al 9 In Ball et al, 10 the proposition ACT-R 11 was designed to support natural language. The architecture proposed in this paper uses symbolic knowledge for data exchange among the main blocks.…”

“…The proposed IVCA of Insaurralde et al 9 enables collaboration among multiple air vehicles. The IVCA is generic, but it aims at the study of aircraft working cooperatively.…”

“…This extension can be used in both simulated and real-time environments. Another equivalent improvement is in the architecture CHREST [27] that was employed in the work of Insurralde et al [30]. In Ball et al [26], the proposition ACT-R was designed to support natural language.…”

“…The methodology of [31] uses a heuristic approach to perform fast movement planning. The concept of planning and decision making are in the propositions of Seleckỳ et al [1] and Insaurralde et al [30], but there is not an implementation description. The work of Sampedro et al [32] shows an implementation where a centralized activity manager is responsible for optimal tasks distribution.…”