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Title: :  Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks
PaperId: :  27783
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 6 2025
DUI:    16.0415/IJARIIE-27783
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Jayadevappa R.S SJM INSTITUTE OF TECHNOLOGY CHITRADURGA
Sushmitha .RSJM INSTITUTE OF TECHNOLOGY CHITRADURGA
Sushmitha .DSJM INSTITUTE OF TECHNOLOGY CHITRADURGA
Samuda .MSJM INSTITUTE OF TECHNOLOGY CHITRADURGA
Sri Nidhi . RSJM INSTITUTE OF TECHNOLOGY CHITRADURGA

Abstract

Electronics and Communication Engineering
Gait phase prediction, locomotion dynamics, proprioceptive data imaging, deep learning models, CNN–RNN architecture, quadruped locomotion, real-time estimation, terrain-adaptive control
Reliable phase estimation plays a crucial role in enabling smooth, adaptive, and disturbance-resistant locomotion in legged robots. Traditional estimation methods often rely on handcrafted features or analytical gait models, which suffer from reduced performance under noisy sensor inputs, terrain variability, and rapid gait transitions. This research proposes a robust and efficient phase estimation framework that leverages signal imaging techniques and deep neural network architectures to learn discriminative gait representations directly from raw proprioceptive signals. Sensor streams—including joint kinematics, actuator feedback, and inertial data—are encoded into 2D image-based signal maps to capture the underlying spatial–temporal structure of locomotion dynamics. A customized CNN–RNN hybrid model is designed to process these signal images, providing accurate, real-time phase predictions with high resilience to disturbances and domain shifts. Experimental results on simulated and real quadruped platforms demonstrate significant improvements in accuracy, generalization, and computational efficiency compared to baseline estimators. This approach offers a scalable solution for next-generation legged robots, enhancing adaptability, terrain awareness, and locomotion stability

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IJARIIE Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. "Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 6 2025 Page 1113-1119
MLA Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. "Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks." International Journal Of Advance Research And Innovative Ideas In Education 11.6(2025) : 1113-1119.
APA Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, & Sri Nidhi . R. (2025). Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks. International Journal Of Advance Research And Innovative Ideas In Education, 11(6), 1113-1119.
Chicago Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. "Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 6 (2025) : 1113-1119.
Oxford Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. 'Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 6, 2025, p. 1113-1119. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Robust_And_Efficient_Phase_Estimation_in_legged_Robots_Via_Signal_Imaging_And_Deep_Neural_Networks_ijariie27783.pdf (Accessed : ).
Harvard Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. (2025) 'Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks', International Journal Of Advance Research And Innovative Ideas In Education, 11(6), pp. 1113-1119IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Robust_And_Efficient_Phase_Estimation_in_legged_Robots_Via_Signal_Imaging_And_Deep_Neural_Networks_ijariie27783.pdf (Accessed : )
IEEE Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R, "Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 6, pp. 1113-1119, Nov-Dec 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/Robust_And_Efficient_Phase_Estimation_in_legged_Robots_Via_Signal_Imaging_And_Deep_Neural_Networks_ijariie27783.pdf [Accessed : ].
Turabian Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. "Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 6 ().
Vancouver Jayadevappa R.S , Sushmitha .R, Sushmitha .D, Samuda .M, and Sri Nidhi . R. Robust And Efficient Phase Estimation in legged Robots Via Signal Imaging And Deep Neural Networks. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(6) : 1113-1119. Available from: https://ijariie.com/AdminUploadPdf/Robust_And_Efficient_Phase_Estimation_in_legged_Robots_Via_Signal_Imaging_And_Deep_Neural_Networks_ijariie27783.pdf
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