The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Neste estudo, sob a suposição de que um robô (1) possui uma câmera de guinada controlável remotamente e (2) se move em um movimento linear uniforme, propomos e investigamos como melhorar a taxa de reconhecimento do alvo com a câmera, usando loop de feedback sem fio ao controle. Derivamos teoricamente a taxa de dados permitida e, do ponto de vista do controle de erros e atrasos, propomos e avaliamos esquemas QoS-Hybrid ARQ sob restrições de taxa de dados. Especificamente, as análises teóricas derivam a taxa máxima de dados para detecção e controle com base na capacidade do canal, derivada do teorema de Shannon-Hartley e do modelo de canal de perda de caminho dentro do corpo humano, ou seja, CM2 no padrão IEEE 802.15.6. Então, os esquemas adaptativos de controle de erro e atraso, ou seja, QoS-HARQ, são propostos considerando as duas restrições: a taxa máxima de dados e a velocidade de movimento da câmera. Para as avaliações de desempenho, com o simulador de robô 3D GAZEBO, avaliamos nossos esquemas propostos nos dois cenários: o ambiente estático e o ambiente dinâmico. Os resultados fornecem insights sobre como melhorar consideravelmente a taxa de reconhecimento em cada situação.
Satoshi SEIMIYA
the Yokohama National University
Takumi KOBAYASHI
the Yokohama National University
Ryuji KOHNO
the Yokohama National University
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Satoshi SEIMIYA, Takumi KOBAYASHI, Ryuji KOHNO, "Dependable Wireless Feedback Loop Control Schemes Considering Errors and Delay in Sensing Data and Control Command Packets" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 6, pp. 1113-1120, June 2019, doi: 10.1587/transcom.2018HMP0008.
Abstract: In this study, under the assumption that a robot (1) has a remotely controllable yawing camera and (2) moves in a uniform linear motion, we propose and investigate how to improve the target recognition rate with the camera, by using wireless feedback loop control. We derive the allowable data rate theoretically, and, from the viewpoint of error and delay control, we propose and evaluate QoS-Hybrid ARQ schemes under data rate constraints. Specifically, the theoretical analyses derive the maximum data rate for sensing and control based on the channel capacity is derived with the Shannon-Hartley theorem and the path-loss channel model inside the human body, i.e. CM2 in IEEE 802.15.6 standard. Then, the adaptive error and delay control schemes, i.e. QoS-HARQ, are proposed considering the two constraints: the maximum data rate and the velocity of the camera's movement. For the performance evaluations, with the 3D robot simulator GAZEBO, we evaluated our proposed schemes in the two scenarios: the static environment and the dynamic environment. The results yield insights into how to improve the recognition rate considerably in each situation.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018HMP0008/_p
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@ARTICLE{e102-b_6_1113,
author={Satoshi SEIMIYA, Takumi KOBAYASHI, Ryuji KOHNO, },
journal={IEICE TRANSACTIONS on Communications},
title={Dependable Wireless Feedback Loop Control Schemes Considering Errors and Delay in Sensing Data and Control Command Packets},
year={2019},
volume={E102-B},
number={6},
pages={1113-1120},
abstract={In this study, under the assumption that a robot (1) has a remotely controllable yawing camera and (2) moves in a uniform linear motion, we propose and investigate how to improve the target recognition rate with the camera, by using wireless feedback loop control. We derive the allowable data rate theoretically, and, from the viewpoint of error and delay control, we propose and evaluate QoS-Hybrid ARQ schemes under data rate constraints. Specifically, the theoretical analyses derive the maximum data rate for sensing and control based on the channel capacity is derived with the Shannon-Hartley theorem and the path-loss channel model inside the human body, i.e. CM2 in IEEE 802.15.6 standard. Then, the adaptive error and delay control schemes, i.e. QoS-HARQ, are proposed considering the two constraints: the maximum data rate and the velocity of the camera's movement. For the performance evaluations, with the 3D robot simulator GAZEBO, we evaluated our proposed schemes in the two scenarios: the static environment and the dynamic environment. The results yield insights into how to improve the recognition rate considerably in each situation.},
keywords={},
doi={10.1587/transcom.2018HMP0008},
ISSN={1745-1345},
month={June},}
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TY - JOUR
TI - Dependable Wireless Feedback Loop Control Schemes Considering Errors and Delay in Sensing Data and Control Command Packets
T2 - IEICE TRANSACTIONS on Communications
SP - 1113
EP - 1120
AU - Satoshi SEIMIYA
AU - Takumi KOBAYASHI
AU - Ryuji KOHNO
PY - 2019
DO - 10.1587/transcom.2018HMP0008
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2019
AB - In this study, under the assumption that a robot (1) has a remotely controllable yawing camera and (2) moves in a uniform linear motion, we propose and investigate how to improve the target recognition rate with the camera, by using wireless feedback loop control. We derive the allowable data rate theoretically, and, from the viewpoint of error and delay control, we propose and evaluate QoS-Hybrid ARQ schemes under data rate constraints. Specifically, the theoretical analyses derive the maximum data rate for sensing and control based on the channel capacity is derived with the Shannon-Hartley theorem and the path-loss channel model inside the human body, i.e. CM2 in IEEE 802.15.6 standard. Then, the adaptive error and delay control schemes, i.e. QoS-HARQ, are proposed considering the two constraints: the maximum data rate and the velocity of the camera's movement. For the performance evaluations, with the 3D robot simulator GAZEBO, we evaluated our proposed schemes in the two scenarios: the static environment and the dynamic environment. The results yield insights into how to improve the recognition rate considerably in each situation.
ER -