TY - GEN
T1 - Optimal Sensor Placement of Variable Impedance Actuated Robots
AU - Rakhim, Bexultan
AU - Zhakatayev, Altay
AU - Adiyatov, Olzhas
AU - Varol, Huseyin Atakan
N1 - Funding Information:
This work was supported by the grant ”Methods for Safe Human Robot Interaction with VIA Robots” from the Ministry of Education and Science of the Republic of Kazakhstan and by the Nazarbayev University Faculty Development Program grant ”Hardware and Software Based Methods for Safe Human-Robot Interaction with Variable Impedance Robots”.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/4/25
Y1 - 2019/4/25
N2 - In this work, we present an optimal sensor placement framework for variable impedance actuated (VIA) robots. Traditionally, sensors are placed on robotic systems to ensure direct measurement of all states. VIA robots have high number of actuators to regulate stiffness, damping and position independently. Therefore, direct measurement of all states requires a high number of sensors increasing the cost, weight and probability of hardware faults. Measuring a subset of states and estimating the rest might be a solution for this problem. However, selecting the subset of states to measure is not straightforward. To tackle this problem, we formulated an optimization problem using the Gramian based observability matrix. The observability of the system with different subsets of sensors is measured for given trajectories and the subset of sensors with the best observability measure is selected. We demonstrated the efficacy of our sensor selection approach in simulation experiments conducted with two variable stiffness actuated robots.
AB - In this work, we present an optimal sensor placement framework for variable impedance actuated (VIA) robots. Traditionally, sensors are placed on robotic systems to ensure direct measurement of all states. VIA robots have high number of actuators to regulate stiffness, damping and position independently. Therefore, direct measurement of all states requires a high number of sensors increasing the cost, weight and probability of hardware faults. Measuring a subset of states and estimating the rest might be a solution for this problem. However, selecting the subset of states to measure is not straightforward. To tackle this problem, we formulated an optimization problem using the Gramian based observability matrix. The observability of the system with different subsets of sensors is measured for given trajectories and the subset of sensors with the best observability measure is selected. We demonstrated the efficacy of our sensor selection approach in simulation experiments conducted with two variable stiffness actuated robots.
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U2 - 10.1109/SII.2019.8700432
DO - 10.1109/SII.2019.8700432
M3 - Conference contribution
AN - SCOPUS:85065638102
T3 - Proceedings of the 2019 IEEE/SICE International Symposium on System Integration, SII 2019
SP - 141
EP - 146
BT - Proceedings of the 2019 IEEE/SICE International Symposium on System Integration, SII 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/SICE International Symposium on System Integration, SII 2019
Y2 - 14 January 2019 through 16 January 2019
ER -