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Duc M. Ngo
Thai Nguyen University of Technology
Computer Science & IT Decision Sciences, Operations Research & Management

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Effectiveness and Limitations of Preprocessing Methods for Proprioceptive Sensor Noise in Quadruped Robots Mui D. Nguyen; Minh T. Nguyen; Ha T. Nguyen; Binh TT. Nguyen; Long Q. Dinh; Dung T. Nguyen; Thang C. Vu; Duc M. Ngo
Journal of Computing Theories and Applications Vol. 3 No. 4 (2026): JCTA 3(4) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.15921

Abstract

Proprioceptive sensor data, including inertial measurement units (IMU), joint encoders, and torque sensors, plays a critical role in state estimation for quadruped robots operating in dynamic and unstructured environments. However, these signals are often degraded by various sources of error, such as high-frequency noise, bias, drift, and contact-induced disturbances, which directly affect estimation accuracy and stability. This study presents a systematic analysis of sensor-specific noise characteristics and evaluates the effectiveness of preprocessing methods tailored to each sensor modality. Specifically, moving average filtering is applied to encoder signals to mitigate noise amplification during differentiation, while first-order low-pass filtering is employed for IMU and torque signals to suppress high-frequency noise. Experimental results on a publicly available quadruped dataset demonstrate that encoder velocity RMSE is reduced by 12.09%, high-frequency energy decreases by 59.63%, and signal-to-noise ratio (SNR) improves by 145.6%. However, variance reductions remain limited (3.39% for IMU and 4.05% for torque), indicating the persistence of impulsive, non-Gaussian noise caused by contact events. These findings highlight that linear preprocessing methods are effective for attenuating high-frequency noise but insufficient for handling non-Gaussian disturbances. The study provides practical insights into the effectiveness and limitations of preprocessing strategies, serving as a foundation for developing more robust signal processing and state estimation frameworks in quadruped robotics.
AN-RPL: Infrastructure-Assisted RPL Enhancement via Distributed Anchor Nodes for Mobile IoT Networks Thang C. Vu; Minh T. Nguyen; Mui D. Nguyen; Long Q. Dinh; Dung T. Nguyen; Duc M. Ngo
Journal of Computing Theories and Applications Vol. 4 No. 1 (2026): JCTA 4(1) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.16184

Abstract

The Internet of Things (IoT) has attracted significant attention from the research community due to its wide range of applications. However, the limited energy, processing capability, storage, and communication capacity of IoT devices require routing solutions that are both lightweight and efficient. To address these constraints, the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) was introduced in 2012 as a routing protocol specifically designed for resource-constrained IoT environments. Although RPL performs reliably in static deployments, its performance degrades considerably in mobile environments because of frequent topology changes, slow Trickle timer convergence, and excessive parent churn. This paper proposes Anchor-Node RPL (AN-RPL), an infrastructure-assisted enhancement of RPL that strategically deploys distributed fixed anchor nodes as stable DODAG roots while requiring only minimal firmware modification on mobile sensor nodes, namely a single anchor-flag check during parent selection. Simulation experiments conducted in Cooja using both OF0 and MRHOF objective functions across four scenarios (static, mobile with one, two, and four anchor nodes) demonstrate that AN-RPL with four anchor nodes improves the Data Delivery Ratio (DDR) by up to 30.6 percentage points, reduces the average hop count by up to 51.2%, lowers parent churn by up to 89.5%, and decreases average energy consumption by up to 14.8% compared with conventional single-root mobile RPL. These results demonstrate that infrastructure-assisted anchor deployment provides an effective and practical approach for improving routing reliability and efficiency in mobile RPL-based IoT networks.
Co-Authors Binh TT. Nguyen Dung T. Nguyen Ha T. Nguyen Long Q. Dinh Minh T. Nguyen Mui D. Nguyen Thang C. Vu