A Flexible Multimodal Sole Sensor for Legged Robot Sensing Complex Ground Information during Locomotion

Recent achievements in the field of computer vision, reinforcement learning, and locomotion control have largely extended legged robots’ maneuverability in complex natural environments. However, little research focuses on sensing and analyzing the physical properties of the ground, which is crucial to robots’ locomotion during their interaction with highly irregular profiles, deformable terrains, and slippery surfaces. A biomimetic, flexible, multimodal sole sensor (FMSS) designed for legged robots to identify the ontological status and ground information, such as reaction force mapping, contact situation, terrain, and texture information, to achieve agile maneuvers was innovatively presented in this paper. The FMSS is flexible and large-loaded (20 Pa–800 kPa), designed by integrating a triboelectric sensing coat, embedded piezoelectric sensor, and piezoresistive sensor array. To evaluate the effectiveness and adaptability in different environments, the multimodal sensor was mounted on one of the quadruped robot’s feet and one of the human feet then traversed through different environments in real-world tests. The experiment’s results demonstrated that the FMSS could recognize terrain, texture, hardness, and contact conditions during locomotion effectively and retrain its sensitivity (0.66 kPa−1), robustness, and compliance. The presented work indicates the FMSS’s potential to extend the feasibility and dexterity of tactile perception for state estimation and complex scenario detection.

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Baseline-free sensor fault detection for piezoelectric array

Journal of Intelligent Material Systems and Structures ◽

10.1177/1045389x211018853 ◽

2021 ◽

pp. 1045389X2110188

Author(s):

Qibo Mao ◽

Yuande Wang ◽

Shizuo Huang

Keyword(s):

Prior Knowledge ◽

Frequency Response Function ◽

Sensor Array ◽

Piezoelectric Element ◽

Piezoelectric Sensor ◽

Steel Beam ◽

Sensor Fault ◽

Pass Filter ◽

Sensor Fault Detection ◽

High Pass

In this study, a new methodology is presented to detect the sensor fault for piezoelectric array based on the filtered frequency response function (FRF) shapes. The proposed method does not require prior knowledge about healthy piezoelectric array. First, the imaginary parts of FRFs from the piezoelectric array during vibration are measured and normalized to obtain the FRF shapes in different frequencies. Then the irregularities in these FRF shapes are extracted by using high-pass filter with properly chosen cut-off frequency. These abnormal irregularities on the filtered FRF shape curves indicate the location of the faulty sensor, due to the irregularity of FRF shapes introduced by the faulty piezoelectric element. The proposed sensor fault method is experimentally demonstrated on a clamped-clamped steel beam mounted with piezoelectric buzzer array. Two common piezoelectric sensor fault types including sensor breakage and debonding are evaluated. The experimental results indicate that the proposed method has great potential in the detection of the sensor fault for piezoelectric array as it is simple and does not require the FRF data of the healthy sensor array as a baseline.

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