scholarly journals Could Active Perception Aid Navigation of Partially Observable Grid Worlds?

2003 ◽  
pp. 72-83 ◽  
Author(s):  
Paul A. Crook ◽  
Gillian Hayes
Keyword(s):  
Active Perception ◽  
Partially Observable

Tire Rolling Kinematics Model for an Intelligent Tire Based on an Accelerometer

2020 ◽  
Vol 48 (4) ◽  
pp. 287-314
Author(s):  
Yan Wang ◽  
Zhe Liu ◽  
Michael Kaliske ◽  
Yintao Wei
Keyword(s):  
Elastic Deformation ◽  
Estimation Algorithm ◽  
Force Sensor ◽  
Euler Method ◽  
Rolling Contact ◽  
Body Motion ◽  
Identification Algorithm ◽  
Active Perception ◽  
Kinematics Model ◽  
Ring Model

ABSTRACT The idea of intelligent tires is to develop a tire into an active perception component or a force sensor with an embedded microsensor, such as an accelerometer. A tire rolling kinematics model is necessary to link the acceleration measured with the tire body elastic deformation, based on which the tire forces can be identified. Although intelligent tires have attracted wide interest in recent years, a theoretical model for the rolling kinematics of acceleration fields is still lacking. Therefore, this paper focuses on an explicit formulation for the tire rolling kinematics of acceleration, thereby providing a foundation for the force identification algorithms for an accelerometer-based intelligent tire. The Lagrange–Euler method is used to describe the acceleration field and contact deformation of rolling contact structures. Then, the three-axis acceleration vectors can be expressed by coupling rigid body motion and elastic deformation. To obtain an analytical expression of the full tire deformation, a three-dimensional tire ring model is solved with the tire–road deformation as boundary conditions. After parameterizing the ring model for a radial tire, the developed method is applied and validated by comparing the calculated three-axis accelerations with those measured by the accelerometer. Based on the features of acceleration, especially the distinct peak values corresponding to the tire leading and trailing edges, an intelligent tire identification algorithm is established to predict the tire–road contact length and tire vertical load. A simulation and experiments are conducted to verify the accuracy of the estimation algorithm, the results of which demonstrate good agreement. The proposed model provides a solid theoretical foundation for an acceleration-based intelligent tire.

scholarly journals The look ahead trace back optimizer for genomic selection under transparent and opaque simulators

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Amini ◽  
Felipe Restrepo Franco ◽  
Guiping Hu ◽  
Lizhi Wang
Keyword(s):  
Genomic Selection ◽  
Genetic Gain ◽  
Genomic Prediction ◽  
In Planta ◽  
Data Set ◽  
Look Ahead ◽  
Trace Back ◽  
New Variant ◽  
The Look ◽  
Partially Observable

AbstractRecent advances in genomic selection (GS) have demonstrated the importance of not only the accuracy of genomic prediction but also the intelligence of selection strategies. The look ahead selection algorithm, for example, has been found to significantly outperform the widely used truncation selection approach in terms of genetic gain, thanks to its strategy of selecting breeding parents that may not necessarily be elite themselves but have the best chance of producing elite progeny in the future. This paper presents the look ahead trace back algorithm as a new variant of the look ahead approach, which introduces several improvements to further accelerate genetic gain especially under imperfect genomic prediction. Perhaps an even more significant contribution of this paper is the design of opaque simulators for evaluating the performance of GS algorithms. These simulators are partially observable, explicitly capture both additive and non-additive genetic effects, and simulate uncertain recombination events more realistically. In contrast, most existing GS simulation settings are transparent, either explicitly or implicitly allowing the GS algorithm to exploit certain critical information that may not be possible in actual breeding programs. Comprehensive computational experiments were carried out using a maize data set to compare a variety of GS algorithms under four simulators with different levels of opacity. These results reveal how differently a same GS algorithm would interact with different simulators, suggesting the need for continued research in the design of more realistic simulators. As long as GS algorithms continue to be trained in silico rather than in planta, the best way to avoid disappointing discrepancy between their simulated and actual performances may be to make the simulator as akin to the complex and opaque nature as possible.

scholarly journals Secure Control in Partially Observable Environments to Satisfy LTL Specifications

2020 ◽  
pp. 1-1
Author(s):  
Bhaskar Ramasubramanian ◽  
Luyao Niu ◽  
Andrew Clark ◽  
Linda Bushnell ◽  
Radha Poovendran
Keyword(s):  
Secure Control ◽  
Partially Observable

Optimal adaptive inspection and maintenance for redundant systems

2021 ◽  
pp. 1748006X2110201
Author(s):  
Chaochao Lin ◽  
Matteo Pozzi
Keyword(s):  
Engineering Systems ◽  
Discounted Cost ◽  
Markov Decision ◽  
Inspection And Maintenance ◽  
And Performance ◽  
Partially Observable ◽  
Series Systems ◽  
Selection Of ◽  
Redundant Systems

Optimal exploration of engineering systems can be guided by the principle of Value of Information (VoI), which accounts for the topological important of components, their reliability and the management costs. For series systems, in most cases higher inspection priority should be given to unreliable components. For redundant systems such as parallel systems, analysis of one-shot decision problems shows that higher inspection priority should be given to more reliable components. This paper investigates the optimal exploration of redundant systems in long-term decision making with sequential inspection and repairing. When the expected, cumulated, discounted cost is considered, it may become more efficient to give higher inspection priority to less reliable components, in order to preserve system redundancy. To investigate this problem, we develop a Partially Observable Markov Decision Process (POMDP) framework for sequential inspection and maintenance of redundant systems, where the VoI analysis is embedded in the optimal selection of exploratory actions. We investigate the use of alternative approximate POMDP solvers for parallel and more general systems, compare their computation complexities and performance, and show how the inspection priorities depend on the economic discount factor, the degradation rate, the inspection precision, and the repair cost.

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