The design and implementation of a target tracking test bed based on WSN

Author(s):  
Wenfeng Luo ◽  
Zhenhua Luo
2009 ◽  
Vol 16 (5) ◽  
pp. 1329-1344 ◽  
Author(s):  
Subir Biswas ◽  
Sonny Gupta ◽  
Fan Yu ◽  
Tao Wu

Robotica ◽  
2004 ◽  
Vol 22 (6) ◽  
pp. 661-679 ◽  
Author(s):  
J. Z. Pan ◽  
R. V. Patel

Sophisticated robotic applications require systems to be reconfigurable at the system level. Aiming at this requirement, this paper presents the design and implementation of a software architecture for a reconfigurable real-time multi-processing system for multi-robot control. The system is partitioned into loosely coupled function units and the data modules manipulated by the function units. Modularized and unified structures of the sub-controllers and controller processes are designed and constructed. All the controller processes run autonomously and intra-sub-controller information exchange is realized by shared data modules that serve as a data repository in the sub-controller. The dynamic data-management processes are responsible for data exchange among sub-controllers and across the computer network. Among sub-controllers there is no explicit temporal synchronization and the data dependencies are maintained by using datum-based synchronization. The hardware driver is constructed as a two-layered system to facilitate adaptation to various robotic hardware systems. A series of effective schemes for software fault detection, fault anticipation and fault termination are accomplished to improve run-time safety. The system is implemented cost-effectively on a QNX real-time operating system (RTOS) based system with a complete PC architecture, and experimentally validated successfully on an experimental dual-arm test-bed. The results indicate that the architectural design and implementation are well suited for advanced application tasks.


2021 ◽  
Vol 1 (1) ◽  
pp. 86-100
Author(s):  
Sofia Ranchordas

Recent EU legislative and policy initiatives aim to offer flexible, innovation-friendly, and future-proof regulatory frameworks. Key examples are the EU Coordinated Plan on AI and the recently published EU AI Regulation Proposal which refer to the importance of experimenting with regulatory sandboxes so as to balance innovation in AI against its potential risks. Originally developed in the Fintech sector, regulatory sandboxes create a test bed for a selected number of innovative projects, by waiving otherwise applicable rules, guiding compliance, or customizing enforcement. Despite the burgeoning literature on regulatory sandboxes and the regulation of AI, the legal, methodological, and ethical challenges of these anticipatory or, at times, adaptive regulatory frameworks have remained understudied. This exploratory article delves into the some of the benefits and intricacies of allowing for experimental instruments in the context of the regulation of AI. This article’s contribution is twofold: first, it contextualizes the adoption of regulatory sandboxes in the broader discussion on experimental approaches to regulation; second, it offers a reflection on the steps ahead for the design and implementation of AI regulatory sandboxes.


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