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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.


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Proceedings ArticleDOI
TL;DR: In this article, the authors propose a simulation-based methodology to analyze the impact of different kinds of sensing and perception errors on the behavior of the autonomous system, and show how to analyze how to evaluate the effect of these errors.
Abstract: Sensing and Perception (S&P) is a crucial component of an autonomous system (such as a robot), especially when deployed in highly dynamic environments where it is required to react to unexpected situations. This is particularly true in case of Autonomous Vehicles (AVs) driving on public roads. However, the current evaluation metrics for perception algorithms are typically designed to measure their accuracy per se and do not account for their impact on the decision making subsystem(s). This limitation does not help developers and third party evaluators to answer a critical question: is the performance of a perception subsystem sufficient for the decision making subsystem to make robust, safe decisions? In this paper, we propose a simulation-based methodology towards answering this question. At the same time, we show how to analyze the impact of different kinds of sensing and perception errors on the behavior of the autonomous system.

6 citations

Proceedings ArticleDOI
16 Oct 2000
TL;DR: In this paper, the authors developed a collision avoidance methodology satisfying the needs of autonomous safety systems considering the dynamics of the robots to protect, which was tested very successfully during the Japanese/German space robot project GETEX in April 1999.
Abstract: Intelligent autonomous robotic systems require efficient safety components to assure system reliability during the entire operation. Especially if commanded over long distances, the robotic system must be able to guarantee the planning of safe and collision free movements independently. Therefore the IRF developed a new collision avoidance methodology satisfying the needs of autonomous safety systems considering the dynamics of the robots to protect. To do this, the collision avoidance system cyclically calculates the actual collision danger of the robots with respect to all static and dynamic obstacles in the environment. If a robot gets in collision danger the methodology immediately starts an evasive action to avoid the collision and guides the robot around the obstacle to its target position. This evasive action is calculated in real-time in a mathematically exact way by solving a quadratic convex optimization problem. The secondary conditions of this optimization problem include the potential collision danger of the robots kinematic chain including all temporarily attached grippers and objects and the dynamic constraints of the robots. The result of the optimization procedure are joint accelerations to apply to prevent the robot from colliding and to guide it to its target position. This methodology has been tested very successfully during the Japanese/German space robot project GETEX in April 1999. During the mission, the collision avoidance system successfully protected the free flying Japanese robot ERA on board the satellite ETS-VII at all times. The experiments showed, that the developed system is fully capable of ensuring the safety of such autonomous robotic systems by actively preventing collisions and generating evasive actions in cases of collision danger.

6 citations

Proceedings ArticleDOI
22 Jun 2015
TL;DR: The AEON-FCS aims to enable agile, high performance, robust operation of single or multiple cooperative UAV performing challenging missions like search and rescue under the forest canopy, delivery in rapidly changing unstructured environments, and ensemble collaboration for robust resilient system operations in hostile environments.
Abstract: The NASA Langley Autonomy Incubator focuses on enabling autonomous, cooperative operations of multiple small Unmanned Aerial Vehicles (UAV) and, more generally, creating autonomous system technologies that change the way people and goods are moved from place to place. To enable rapid test and deployment of autonomous algorithms an avionics system is under development. The system, called the Autonomous Entity Operations Network Flight Control System (AEON-FCS), is being developed to be capable of implementing both classic Guidance, Navigation, and Control (GNC) law algorithms in a monolithic system architecture and also a network connected fully distributed control system. AEON-FCS is a subset of the overall AEON system that includes the Avionics System for Remotely Operated Vehicles LiTe (ASROV-LT) codebase and additional data centric tools for distributed control implementation and rapid simulation and testing. The ASROV-LT codebase provides utilities for hard real-time flight control loop processing and serialized sensor parsing. To enable rapid testing of autonomous algorithms, AEON-FCS provides seamless integration between simulation and hardware by utilizing a data centric inter-process communication approach and a global data bus available on the network. A goal for the AEON-FCS is to enable implementation of fully distributed control. Processing locations may be paired with sensors and distributed across either an airframe or across different air and/or ground vehicles on the network connected system. AEON-FCS aims to enable agile, high performance, robust operation of single or multiple cooperative UAV performing challenging missions like search and rescue under the forest canopy, delivery in rapidly changing unstructured environments (rescue in burning building), and ensemble collaboration for robust resilient system operations in hostile environments. The current state of the structure, function, and novel features of the AEON-FCS are described herein.

6 citations

Journal ArticleDOI
TL;DR: In this article, the authors introduce the terms autonomous control, infrastructure, configuration, and logistic system in the application area of production logistics and suggest a conceptual model for modeling infrastructures in general.
Abstract: Autonomous control can increase the flexibility and the robustness of logistic systems by enabling decision making and execution about the system behavior at the system elements themselves. Therefore, logistic systems require specific infrastructure components. This paper presents terms and drivers which are relevant for the configuration of the infrastructure of autonomous logistic control systems. First, it introduces the terms autonomous control, infrastructure, configuration, and logistic system in the application area of production logistics. Second, a control system's macro and micro architecture are discussed. Third, the paper suggests a conceptual model for modeling infrastructures in general.

6 citations

Journal ArticleDOI
TL;DR: It is clearly shown that in case of the introduced static conditions the approach is applicable to determine the optimal solution of the traffic distribution problem in a given sample time period of an autonomous transportation system.
Abstract: The aim of this article is to present the research results of the authors in the field of defining the system optimum regarding the traffic distribution assuming an intelligent and autonomous transportation system. Authors define the linear programming framework of the traffic distribution problem in case of pre-defined demand structure, network properties and alternative routes related to each origin-destination zone pair. In the paper the description of the applied method and its verification are presented in a simplified model example. As a basic result, it is clearly shown that in case of the introduced static conditions the approach is applicable to determine the optimal solution of the traffic distribution problem in a given sample time period of an autonomous transportation system.

6 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202315
202228
202167
202081
2019101
201863