TY - GEN
T1 - Detecting the Distribution of a Robotic Swarm in Uncertain Conditions
AU - Cohen, Eliashiv
AU - Idelson, Yakov
AU - Median, Oded
AU - Shvalb, Nir
AU - Hacohen, Shlomi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Localization problem of a swarm is required for most tasks related to swarms. In many cases real world sensors possess inherent measurement error. Nevertheless, having a large set of inter-measurements may compensate for this. The paper implements Extended Kalman Filter to estimate the swarm's distribution. Indeed, a set of simulated experiments demonstrate the algorithm robustness and simplicity. Finally, we show that the resulting error estimation is reliable.
AB - Localization problem of a swarm is required for most tasks related to swarms. In many cases real world sensors possess inherent measurement error. Nevertheless, having a large set of inter-measurements may compensate for this. The paper implements Extended Kalman Filter to estimate the swarm's distribution. Indeed, a set of simulated experiments demonstrate the algorithm robustness and simplicity. Finally, we show that the resulting error estimation is reliable.
KW - probability-density-function
KW - robotic-swarm
KW - swarm-distribution
UR - http://www.scopus.com/inward/record.url?scp=85081068084&partnerID=8YFLogxK
U2 - 10.1109/ICCMA46720.2019.8988677
DO - 10.1109/ICCMA46720.2019.8988677
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AN - SCOPUS:85081068084
T3 - 2019 IEEE 7th International Conference on Control, Mechatronics and Automation, ICCMA 2019
SP - 104
EP - 107
BT - 2019 IEEE 7th International Conference on Control, Mechatronics and Automation, ICCMA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE International Conference on Control, Mechatronics and Automation, ICCMA 2019
Y2 - 6 November 2019 through 8 November 2019
ER -