scholarly journals Estimation and Planning of Exploration Over Grid Map Using A Spatiotemporal Model with Incomplete State Observations

Author(s):  
Hyung-Jin Yoon ◽  
Hunmin Kim ◽  
Kripash Shrestha ◽  
Naira Hovakimyan ◽  
Petros Voulgaris
Chemosphere ◽  
2020 ◽  
Vol 246 ◽  
pp. 125563 ◽  
Author(s):  
Ting Zhang ◽  
Penghui Liu ◽  
Xue Sun ◽  
Can Zhang ◽  
Meng Wang ◽  
...  

2021 ◽  
Vol 90 ◽  
pp. 103277
Author(s):  
Xiaoying Jiao ◽  
Jason Li Chen ◽  
Gang Li

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
M. D. Robertson ◽  
J. Gao ◽  
P. M. Regular ◽  
M. J. Morgan ◽  
F. Zhang

AbstractAnomalous local temperature and extreme events (e.g. heat-waves) can cause rapid change and gradual recovery of local environmental conditions. However, few studies have tested whether species distribution can recover following returning environmental conditions. Here, we tested for change and recovery of the spatial distributions of two flatfish populations, American plaice (Hippoglossoides platessoides) and yellowtail flounder (Limanda ferruginea), in response to consecutive decreasing and increasing water temperature on the Grand Bank off Newfoundland, Canada from 1985 to 2018. Using a Vector Autoregressive Spatiotemporal model, we found the distributions of both species shifted southwards following a period when anomalous cold water covered the northern sections of the Grand Bank. After accounting for density-dependent effects, we observed that yellowtail flounder re-distributed northwards when water temperature returned and exceeded levels recorded before the cold period, while the spatial distribution of American plaice has not recovered. Our study demonstrates nonlinear effects of an environmental factor on species distribution, implying the possibility of irreversible (or hard-to-reverse) changes of species distribution following a rapid change and gradual recovery of environmental conditions.


Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 920
Author(s):  
Liesle Caballero ◽  
Álvaro Perafan ◽  
Martha Rinaldy ◽  
Winston Percybrooks

This paper deals with the problem of determining a useful energy budget for a mobile robot in a given environment without having to carry out experimental measures for every possible exploration task. The proposed solution uses machine learning models trained on a subset of possible exploration tasks but able to make predictions on untested scenarios. Additionally, the proposed model does not use any kinematic or dynamic models of the robot, which are not always available. The method is based on a neural network with hyperparameter optimization to improve performance. Tabu List optimization strategy is used to determine the hyperparameter values (number of layers and number of neurons per layer) that minimize the percentage relative absolute error (%RAE) while maximize the Pearson correlation coefficient (R) between predicted data and actual data measured under a number of experimental conditions. Once the optimized artificial neural network is trained, it can be used to predict the performance of an exploration algorithm on arbitrary variations of a grid map scenario. Based on such prediction, it is possible to know the energy needed for the robot to complete the exploration task. A total of 128 tests were carried out using a robot executing two exploration algorithms in a grid map with the objective of locating a target whose location is not known a priori by the robot. The experimental energy consumption was measured and compared with the prediction of our model. A success rate of 96.093% was obtained, measured as the percentage of tests where the energy budget suggested by the model was enough to actually carry out the task when compared to the actual energy consumed in the test, suggesting that the proposed model could be useful for energy budgeting in actual mobile robot applications.


Author(s):  
Myung-Joong Jeon ◽  
Hyun-Kyu Park ◽  
Batselem Jagvaral ◽  
Hyung-Sik Yoon ◽  
Yun-Geun Kim ◽  
...  

2015 ◽  
Vol 9 (3) ◽  
pp. 1194-1225 ◽  
Author(s):  
Lasse Holmström ◽  
Liisa Ilvonen ◽  
Heikki Seppä ◽  
Siim Veski

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Zhaowei Qu ◽  
Yan Xing ◽  
Hongyu Hu ◽  
Yuzhou Duan ◽  
Xianmin Song ◽  
...  

The motion characteristics of the leading vehicle and the following vehicles of the traffic flow at the typical urban intersections are qualitatively analyzed through the kinematical equation and the traffic wave theory. Then, the motion characteristic of the whole traffic flow during the dispersion process is also studied. Based on the spatiotemporal model of kinematics in the departure process and traffic wave model in the dispersion process proposed, the change of the leading vehicle of the departure process and the time of the following vehicles reaching to the stable speed as well as the relationship between the green time and the departure vehicle number at the intersection are acquired. Furthermore, according to the qualitative analysis and the quantitative calculation of the departure traffic flow at the signalized intersection, the dispersion characteristic of traffic flow at the signalized intersection was studied and analyzed, which provides reliable theoretical basis for traffic signal setting at the intersection.


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