TY - GEN
T1 - A mechanical lower limb exoskeleton prototype synthetized with a deep learning based Algorithm
AU - Mercader, Alexandra
AU - Laudahn, Simon
AU - Lueth, Tim C.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - This paper deals with kinematic synthesis of a mechanical lower limb given a specific closed path and the corresponding orientation of a human's foot. The purpose of this work is to find a linkage that simulates natural motion, particularly walking, actuated by only one motor. Path and orientation optimization is performed by using a deep learning algorithm combined with a normalization process, which makes it possible to compare and assess the different curves generated by a four-bar mechanism. The resulting regression function approximates the lengths of a four-bar linkage with a mean-square error of 0.01 for a particular shape of four-bar linkage. The difference between the estimated path and the targeted one for this shape is of 0.13, scaled for a unit length of the four-bar's ground link, and for the orientation of 0.40 radians. In the examples presented in this paper, this algorithm returns the dimensions of four-bar linkages that generate a near-walking path, while taking the orientation of the foot into account. The results obtained with real measurements lead to the concept of a mechanical lower limb.
AB - This paper deals with kinematic synthesis of a mechanical lower limb given a specific closed path and the corresponding orientation of a human's foot. The purpose of this work is to find a linkage that simulates natural motion, particularly walking, actuated by only one motor. Path and orientation optimization is performed by using a deep learning algorithm combined with a normalization process, which makes it possible to compare and assess the different curves generated by a four-bar mechanism. The resulting regression function approximates the lengths of a four-bar linkage with a mean-square error of 0.01 for a particular shape of four-bar linkage. The difference between the estimated path and the targeted one for this shape is of 0.13, scaled for a unit length of the four-bar's ground link, and for the orientation of 0.40 radians. In the examples presented in this paper, this algorithm returns the dimensions of four-bar linkages that generate a near-walking path, while taking the orientation of the foot into account. The results obtained with real measurements lead to the concept of a mechanical lower limb.
UR - http://www.scopus.com/inward/record.url?scp=85089541757&partnerID=8YFLogxK
U2 - 10.1109/CBS46900.2019.9114492
DO - 10.1109/CBS46900.2019.9114492
M3 - Conference contribution
AN - SCOPUS:85089541757
T3 - 2019 IEEE International Conference on Cyborg and Bionic Systems, CBS 2019
SP - 316
EP - 321
BT - 2019 IEEE International Conference on Cyborg and Bionic Systems, CBS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Cyborg and Bionic Systems, CBS 2019
Y2 - 18 September 2019 through 20 September 2019
ER -