Electrospining: Gait sensor with custom protrusions for quadruped robots

Background

Stable data acquisition and accurate motion state recognition are key to bionic robots working in complex environments. Professor Guozhen Shen of Beijing Institute of Technology and Professor Bin Sun of Qingdao University have collaborated to propose a flexible gait sensor capable of detecting pressure and vibration of quadruped robots. These sensors are manufactured using template-restricted electrospinning technology, allowing for direct customization of protruding structures. The relevant research results were published in the journal Advanced Fiber Materials (IF 17.2) under the title "Gait Sensors with Customized Protruding Structures for Quadruped Robot Applications".

The main point of this paper

1. This study proposes a flexible gait sensor that can detect pressure and vibration of quadruped robots. These sensors are fabricated using template-confined electrospinning technology.

2. The developed gait sensor has a maximum capacitive sensitivity of 1.237 kPa⁻¹, a detection range extended to 1000 kPa, and a response time of 5 ms.

3. Taking advantage of their lightweight characteristics, these sensors can detect vibrations under various weight loads, frequencies, and amplitudes.

In addition, the recognition process combining these gait sensors with deep learning technology for quadruped robot applications was studied. It demonstrated the ability of the sensor to monitor different motion postures and states of the robot, achieving up to 97.50% gait recognition accuracy and 98.04% abnormal interference accuracy.

What are the key features of the flexible gait sensor developed in this study?

1.Customization: The sensors are fabricated using template-restricted electrospinning technology, which allows for direct customization of the protrusion structure, thereby enhancing its sensitivity and performance.

2.High sensitivity: The sensors have a maximum capacitive sensitivity of 1.237 kPa⁻¹, enabling them to detect small changes in pressure and vibration.

3. Wide detection range: Their detection range can be extended to 1000 kPa, making them suitable for a wide range of applications and conditions.

4.Fast response time: The sensors have a response time of approximately 5 milliseconds, which is critical for monitoring rapidly changing vibrations.

5.Stability and durability: The sensors maintain their performance after a large number of loading and unloading cycles, demonstrating excellent stability and the ability to return to their original shape due to the elastic properties of the TPU nanofibers.

Effective motion recognition: When combined with a deep learning model, the sensors were able to achieve up to 97.50% gait recognition accuracy and 98.04% abnormal interference detection accuracy, demonstrating their effectiveness in monitoring the robot's diverse motion postures and states.

 How can gait sensors improve the performance of quadruped robots in complex environments?

1. Real-time monitoring: The sensor provides a fast response time of about 5 milliseconds, allowing the robot to monitor its movements and surroundings in real time.

2. Pressure and vibration detection: By detecting pressure and vibration, the sensor is able to evaluate the robot's interaction with various surfaces and obstacles. This information helps the robot adjust its gait and posture accordingly, thereby improving stability and maneuverability in complex terrain.

3. High sensitivity and wide detection range: The sensor has a capacitive sensitivity of up to 1.237 kPa-1 and a wide detection range of up to 1000 kPa, enabling it to detect small changes in the environment. This sensitivity enables the robot to react to different ground conditions, such as soft or uneven surfaces, thereby enhancing its adaptability.

4. Integration with deep learning: The combination of sensor data and deep learning technology enables advanced gait recognition and abnormal interference identification. This integration enables the robot to learn from the environment and improve its performance over time, with gait recognition accuracy as high as 97.50%.

5.Enhanced stability and safety: The sensor remains structurally stable under repeated loading and unloading, which is critical for long-term operation under various conditions. This durability ensures that the robot can operate safely and efficiently without the need for frequent sensor replacement.

6. Adaptation to different gaits: The sensor is able to analyze and summarize the robot's motion characteristics in different gaits (such as slow walking, running, jumping). This ability enables the robot to adjust its motion strategy according to the specific needs of the environment, thereby improving overall performance.