A blackboard system approach to electromagnetic sensor data interpretation

1998 ◽  
Vol 15 (3) ◽  
pp. 197-215 ◽  
Author(s):  
S.M.C. Peers
Author(s):  
Takeshi Semba ◽  
Hideaki Osawa ◽  
Kazumasa Hioki ◽  
Shoko Tachibana ◽  
Hiroyasu Takase ◽  
...  

The characterisation of potential repository sites will produce huge volumes of information, which must be correlated, quality assured, integrated, analysed, documented and archived in a rigorous and efficient manner. While some of this work involves rather routine data handling that may be easily automated, much of it requires input of tacit knowledge which involves the experience of expert staff. To provide support for the Japanese implementer and also the regulator, a JAEA team is attempting to capture both Japanese and international geosynthesis experience within a Knowledge Management System (KMS) framework, which is termed ISIS. This is a hybrid system that combines “smart” software with human experts, although an aim is to capture tacit knowledge within expert systems to the maximum extent practicable. Initial tests, based mainly on field work carried out by JAEA at the sites of the Mizunami and Horonobe underground research laboratories, have utilised expert systems as modules in a “blackboard system” approach to planning or implementing the processing of field data. Examples are presented of sub-systems where this approach has already been demonstrated and perspectives for more extensive application to integrated geosynthesis management are discussed.


2014 ◽  
Vol 15 (5) ◽  
pp. 263-286 ◽  
Author(s):  
Petter Almklov ◽  
◽  
Thomas Østerlie ◽  
Torgeir Haavik ◽  
◽  
...  

2017 ◽  
Vol 8 (2) ◽  
pp. 461-465 ◽  
Author(s):  
D. Whattoff ◽  
A. Mouazen ◽  
T. Waine

In this research a multi-sensor and data fusion approach was developed to create variable depth tillage zones. Data collected with an electromagnetic sensor was fused with measurements taken with a hydraulic penetrometer and conventionally acquired soil bulk density (BD) and moisture content (MC) measurements. Packing density values were then calculated for eight soil layers to determine the need to cultivate or not. From the results 62% of the site required the deepest tillage at 38 cm, 16% required tillage at 33 cm and 22% required no tillage at all. The resultant maps of packing density were shown to be a useful approach to map layered soil compaction and guide VDT operations.


2004 ◽  
Vol 01 (02) ◽  
pp. 289-314 ◽  
Author(s):  
R. ANDREW RUSSELL ◽  
GEOFFREY TAYLOR ◽  
LINDSAY KLEEMAN ◽  
ANIES H. PURNAMADJAJA

Sensing is a key element for any intelligent robotic system. This paper describes the current progress of a project in the Intelligent Robotics Research Center at Monash University that has the aim of developing a synergistic set of sensory systems for a humanoid robot. Currently, sensing modes for colour vision, stereo vision, active range, smell and airflow are being developed in a size and form that is compatible with the humanoid appearance. Essential considerations are sensor calibration and the processing of sensor data to give reliable information about properties of the robot's environment. In order to demonstrate the synergistic use of all of the available sensory modes, a high level supervisory control scheme is being developed for the robot. All time-stamped sensor data together with derived information about the robot's environment are organized in a blackboard system. Control action sequences are then derived from the blackboard data based on a task description. The paper presents details of each of the robot's sensory systems, sensor calibration, and supervisory control. Results are also presented of a demonstration project that involves identifying and selecting mugs containing household chemicals. Proposals for future development of the humanoid robot are also presented.


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