3.1 Resistive strain sensors
12 min read•august 20, 2024
Resistive strain sensors are crucial for measuring deformation in soft robotics. These sensors change electrical resistance when stretched, allowing robots to sense their own movements and interactions. Various types exist, from conductive elastomers to liquid metals, each with unique properties.
Choosing the right sensor involves balancing factors like sensitivity, stretchability, and durability. Fabrication methods range from mixing conductive fillers into elastomers to 3D printing embedded sensors. Understanding sensor properties and challenges is key to effective soft robot design and control.
Types of resistive strain sensors
- Resistive strain sensors are devices that change electrical resistance when subjected to mechanical strain, enabling the measurement of deformation in soft materials and structures
- Several types of resistive strain sensors have been developed for soft robotics applications, each with unique properties and fabrication methods
- The choice of strain sensor type depends on factors such as the required sensitivity, stretchability, durability, and compatibility with the soft robot materials and manufacturing process
Conductive elastomers for strain sensing
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- Conductive elastomers are polymer materials that exhibit a change in electrical resistance when stretched or compressed
- These materials are typically fabricated by mixing conductive fillers (carbon black, carbon nanotubes, graphene) into an elastomeric matrix (silicone, polyurethane)
- The conductive filler forms a percolating network within the elastomer, and the resistance changes as the network is deformed under strain
- Conductive elastomer strain sensors can be highly stretchable (up to 100% strain) and conformable to complex shapes
- Examples: Carbon black-filled silicone, CNT-filled polyurethane
Liquid metal strain sensors
- Liquid metal strain sensors utilize the deformation of microchannels filled with conductive liquid metal (gallium-indium alloys) to measure strain
- As the soft material is stretched, the geometry of the microchannels changes, causing a change in the electrical resistance of the liquid metal
- Liquid metal strain sensors can achieve high sensitivity and stretchability, as the liquid can flow and maintain conductivity under large deformations
- The sensors are typically fabricated by molding microchannels in a soft elastomer and injecting the liquid metal into the channels
- Examples: EGaIn-filled microchannels in PDMS, Galinstan-filled microchannels in Ecoflex
Conductive fabric strain sensors
- Conductive fabric strain sensors are made by incorporating conductive yarns (stainless steel, silver-coated nylon) or coatings (, carbon nanotubes) into textile structures
- The resistance of the conductive fabric changes as the textile is stretched, allowing for strain sensing in soft, flexible, and breathable materials
- Conductive fabric sensors can be easily integrated into wearable devices and soft exosuits for human motion tracking and assistive applications
- The sensors are fabricated by knitting, weaving, or embroidering conductive yarns into fabric patterns or by coating conventional fabrics with conductive materials
- Examples: Silver-coated nylon knitted strain sensor, PEDOT:PSS-coated spandex fabric sensor
Resistive ink strain sensors
- Resistive ink strain sensors are fabricated by printing conductive inks (carbon, silver, conductive polymers) onto stretchable substrates (thermoplastic polyurethane, silicone)
- As the substrate is stretched, the printed ink pattern deforms, causing a change in electrical resistance that can be correlated to strain
- Resistive ink sensors can be patterned into various geometries and integrated with other printed electronic components for soft, flexible sensing systems
- The sensors are fabricated using additive manufacturing techniques such as screen printing, inkjet printing, and aerosol jet printing
- Examples: Carbon-based resistive ink printed on TPU substrate, silver nanoparticle ink printed on PDMS
Properties of resistive strain sensors
- The performance of resistive strain sensors is characterized by several key properties that determine their suitability for different soft robotics applications
- Understanding these properties is essential for selecting the appropriate strain sensor type and designing effective soft sensing systems
- The main properties of interest include , , linearity, repeatability, and drift, which collectively influence the accuracy, precision, and reliability of strain measurements
Gauge factor of strain sensors
- Gauge factor (GF) is a measure of the sensitivity of a strain sensor, defined as the ratio of relative change in electrical resistance to the applied mechanical strain
- A higher gauge factor indicates a larger change in resistance for a given strain, enabling the detection of smaller deformations
- Gauge factor is influenced by the sensor material composition, microstructure, and geometry, and can be optimized through material selection and design
- Typical gauge factors for resistive strain sensors range from 1-10 for conductive elastomers and fabrics, to 50-100 for liquid metal and printed ink sensors
- Examples: Carbon nanotube-based strain sensors with GF ~50, liquid metal sensors with GF ~100
Hysteresis in strain sensors
- Hysteresis refers to the difference in the strain-resistance relationship between the loading and unloading cycles of a strain sensor
- Ideally, a strain sensor should exhibit minimal hysteresis, meaning that the resistance at a given strain is the same during both loading and unloading
- Hysteresis can arise from viscoelastic effects in the sensor materials, as well as from the irreversible deformation of conductive networks or interfaces
- High hysteresis can lead to inaccuracies in strain measurements and may require complex compensation methods in sensor data processing
- Examples: Conductive elastomer sensors with hysteresis <10% strain, printed resistive ink sensors with hysteresis <5% strain
Linearity of strain response
- Linearity refers to the degree to which the change in resistance of a strain sensor is directly proportional to the applied strain
- A linear strain response simplifies the calibration and data interpretation of the sensor, as the strain can be directly calculated from the measured
- Non-linear strain responses can arise from the non-uniform deformation of the conductive networks, the saturation of conductive pathways, or the change in contact resistance between conductive elements
- Linearity can be improved by optimizing the sensor material composition, geometry, and fabrication process to ensure a uniform and stable conductive network
- Examples: Liquid metal sensors with linear response up to 50% strain, conductive fabric sensors with linear response up to 30% strain
Repeatability of strain measurements
- Repeatability refers to the ability of a strain sensor to produce consistent resistance measurements under repeated cycles of loading and unloading
- High repeatability is essential for reliable strain monitoring in soft robotics applications, particularly in systems that undergo cyclic deformations
- Repeatability can be affected by factors such as the mechanical fatigue of the sensor materials, the stability of the conductive networks, and the adhesion between the sensor and the substrate
- Strategies for improving repeatability include using durable and fatigue-resistant materials, optimizing the sensor fabrication process, and ensuring robust sensor-substrate interfaces
- Examples: Carbon nanotube-based strain sensors with repeatability over 10,000 cycles, printed silver ink sensors with repeatability over 1,000 cycles
Drift in strain sensor readings
- Drift refers to the gradual change in the resistance of a strain sensor over time, even under constant strain conditions
- Drift can be caused by the viscoelastic relaxation of the sensor materials, the degradation of the conductive networks, or the influence of environmental factors such as temperature and humidity
- Drift can lead to inaccuracies in long-term strain monitoring applications and may require periodic recalibration or compensation techniques
- Minimizing drift requires the use of stable and environmentally resistant sensor materials, as well as proper encapsulation and protection of the sensors
- Examples: Conductive elastomer sensors with drift <1% per day, liquid metal sensors with drift <0.5% per hour
Fabrication of resistive strain sensors
- The fabrication process for resistive strain sensors plays a crucial role in determining their performance, reliability, and integration with soft robotic systems
- Various fabrication techniques have been developed to create strain sensors with different materials, geometries, and sensing properties
- The choice of fabrication method depends on factors such as the desired sensor resolution, the compatibility with soft robot manufacturing processes, and the scalability for large-scale production
Materials for resistive strain sensors
- A wide range of materials can be used to fabricate resistive strain sensors, each with unique electrical, mechanical, and chemical properties
- Conductive fillers such as carbon black, carbon nanotubes, and graphene are commonly used to impart electrical conductivity to elastomeric matrices like silicone and polyurethane
- Liquid metals, such as gallium-indium alloys, are used in microfluidic strain sensors due to their high conductivity and ability to maintain electrical continuity under large deformations
- Conductive inks, including carbon-based and metallic nanoparticle inks, are used in printed strain sensors for their compatibility with additive manufacturing processes
- Examples: Carbon black-filled silicone elastomers, eutectic gallium-indium (EGaIn) liquid metal, silver nanoparticle conductive inks
Patterning techniques for strain sensors
- Patterning techniques are used to define the geometry and spatial distribution of the conductive elements in resistive strain sensors
- Photolithography is a high-resolution patterning method that involves selectively exposing a photosensitive material to create a desired pattern, which can be transferred to the sensor material
- Screen printing is a versatile technique for depositing conductive inks or pastes onto substrates through a patterned mesh, enabling the fabrication of large-area strain sensors
- Laser cutting can be used to create intricate patterns in conductive films or fabrics, allowing for the design of custom strain sensor geometries
- Examples: Photolithographically-patterned liquid metal sensors, screen-printed carbon ink sensors, laser-cut conductive fabric sensors
Embedding strain sensors in soft materials
- Embedding strain sensors directly into the soft materials of a robot allows for seamless integration and improved strain transfer between the sensor and the robot structure
- Sensors can be embedded by casting the soft material (e.g., silicone elastomer) around the pre-fabricated sensor, ensuring a strong mechanical bond between the sensor and the surrounding material
- 3D printing techniques, such as direct ink writing or fused deposition modeling, can be used to fabricate soft structures with embedded strain sensors in a single step
- Challenges in embedding sensors include ensuring proper alignment, preventing damage to the sensor during the embedding process, and maintaining the desired mechanical properties of the soft material
- Examples: Conductive elastomer sensors embedded in silicone pneumatic actuators, 3D-printed strain sensors embedded in soft robotic grippers
Bonding strain sensors to substrates
- In some cases, strain sensors are fabricated separately and then bonded to the surface of a soft robotic structure
- Bonding methods should provide a strong, stable adhesion between the sensor and the substrate to ensure efficient strain transfer and prevent delamination
- Adhesive bonding involves using a thin layer of adhesive material, such as silicone or epoxy, to attach the sensor to the substrate
- Plasma bonding is a method that uses plasma treatment to activate the surfaces of the sensor and substrate, promoting strong covalent bonding when the surfaces are brought into contact
- Challenges in bonding sensors include achieving uniform adhesion, minimizing the effect of the adhesive layer on the sensor performance, and ensuring compatibility between the adhesive and the sensor and substrate materials
- Examples: Liquid metal sensors bonded to silicone substrates using oxygen plasma treatment, conductive fabric sensors bonded to textile substrates using silicone adhesive
Wiring and connections for strain sensors
- Robust and reliable electrical connections are essential for integrating strain sensors into soft robotic systems and enabling
- Wiring methods should be flexible and stretchable to accommodate the deformation of the soft robot without constraining its motion or causing damage to the connections
- Stretchable conductive materials, such as serpentine metal traces or conductive polymer composites, can be used to create flexible interconnects between the sensors and the data acquisition electronics
- Conductive threads or yarns can be used to create textile-based interconnects for wearable strain sensing applications
- Challenges in wiring include maintaining electrical continuity under repeated stretching and bending, minimizing the effect of the wires on the mechanical properties of the soft robot, and preventing damage to the wires during fabrication and operation
- Examples: Serpentine silver traces for connecting liquid metal sensors, conductive thread interconnects for textile-based strain sensors
Applications of resistive strain sensors
- Resistive strain sensors have found numerous applications in soft robotics, enabling the measurement of deformation, motion, and interaction forces in compliant structures and devices
- The unique properties of soft strain sensors, such as high stretchability, conformability, and compliance, make them well-suited for monitoring the behavior of soft robots and their interactions with the environment
- Strain sensors can be integrated into various soft robotic systems, including actuators, grippers, wearable devices, and bio-inspired robots, to provide valuable feedback for control, automation, and user interaction
Strain sensors for motion tracking
- Strain sensors can be used to track the motion and posture of soft robots, providing real-time information on the deformation and kinematics of the robot structure
- By strategically placing strain sensors on soft actuators, such as pneumatic bellows or dielectric elastomer actuators, the bending angle, extension, or contraction of the actuator can be measured
- Strain sensors can also be integrated into soft wearable devices, such as gloves or exosuits, to track human body movements for applications in virtual reality, teleoperation, or rehabilitation monitoring
- Examples: Liquid metal strain sensors for measuring the bending angle of a soft pneumatic actuator, conductive fabric strain sensors for tracking hand gestures in a soft robotic glove
Strain sensors for force sensing
- Strain sensors can be used to measure the interaction forces between a soft robot and its environment, enabling force feedback and control
- By calibrating the strain sensor response to applied forces, the deformation of the soft robot structure can be correlated to the magnitude and distribution of the contact forces
- Force-sensitive strain sensors can be integrated into soft robotic grippers to detect grasping forces and optimize the gripping strategy for delicate or variable objects
- Strain sensors can also be used to measure the ground reaction forces in soft legged robots, providing feedback for gait control and stability
- Examples: Resistive ink strain sensors for measuring grasping forces in a soft robotic hand, conductive elastomer strain sensors for detecting ground contact in a soft quadruped robot
Strain sensors in wearable devices
- Strain sensors are particularly well-suited for integration into soft wearable devices due to their flexibility, stretchability, and conformability to the human body
- Wearable strain sensors can be used to monitor human body movements, posture, and gestures for applications in healthcare, sports, and human-machine interaction
- Strain sensors can be embedded into soft exosuits or assistive devices to detect the user's motion and provide feedback for control and actuation
- Wearable strain sensors can also be used for physiological monitoring, such as measuring respiration rate or detecting muscle activity
- Examples: Conductive fabric strain sensors for monitoring knee joint motion in a soft exosuit, printed resistive ink strain sensors for detecting hand gestures in a wearable controller
Strain sensors for structural health monitoring
- Strain sensors can be used to monitor the structural health and integrity of soft robotic systems, detecting damage, fatigue, or excessive deformation
- By embedding strain sensors into the soft robot structure, the distribution of strains can be measured and compared to expected values or failure thresholds
- with strain sensors can enable predictive maintenance, improving the reliability and lifespan of soft robots
- Strain sensors can also be used to detect and localize damage, such as tears or punctures, in soft inflatable structures
- Examples: Carbon nanotube-based strain sensors for monitoring the health of a soft pneumatic actuator, liquid metal strain sensors for detecting damage in a soft robotic gripper
Strain feedback for soft robot control
- Strain sensor feedback can be used to improve the control and automation of soft robotic systems, enabling more precise and adaptive motion
- By measuring the actual deformation of soft actuators, strain sensors can provide closed-loop feedback for controlling the position, force, or stiffness of the robot
- Strain feedback can be used to compensate for the nonlinear and time-varying behavior of soft materials, improving the accuracy and repeatability of soft robot motion
- Strain sensors can also enable the implementation of advanced control strategies, such as impedance control or learning-based control, in soft robotic systems
- Examples: Conductive elastomer strain sensors for closed-loop position control of a soft pneumatic bending actuator, liquid metal strain sensors for force control in a soft robotic gripper
Challenges with resistive strain sensors
- Despite the numerous advantages and applications of resistive strain sensors in soft robotics, several challenges must be addressed to ensure their reliable and effective use
- These challenges relate to the long-term performance, environmental sensitivity, and integration of strain sensors into soft robotic systems
- Addressing these challenges requires a multidisciplinary approach, combining advances in materials science, fabrication technologies, and signal processing techniques
Strain sensor durability and fatigue
- Soft robotic systems often undergo repeated cycles of large deformations, which can cause mechanical fatigue and degradation of the strain sensors over time
- The conductive materials and structures in the strain sensors, such as conductive fillers or printed traces, can experience damage, cracking, or delamination under cyclic loading
- Fatigue can lead to changes in the sensor's response, such as reduced sensitivity, increased hysteresis, or complete failure
- Improving strain sensor durability requires the development of robust and fatigue-resistant materials, such as self-healing conductors or nanocomposite elastomers
- Examples: Self-healing liquid metal strain sensors with improved fatigue resistance, carbon nanotube-based strain sensors with high durability over 10,000 cycles
Strain sensor sensitivity vs robustness
- There is often a trade-off between the sensitivity and robustness of strain sensors in soft robotic applications
- Highly sensitive strain sensors, such as those based on nanomaterials or microstructured conductors, can detect small deformations but may be more susceptible to
Key Terms to Review (18)
3D printed sensors: 3D printed sensors are advanced devices that utilize additive manufacturing techniques to create intricate sensor components and structures. This technology allows for the production of customized sensors with complex geometries, enabling applications in various fields, including soft robotics, where flexibility and adaptability are essential.
ASTM Testing Methods: ASTM testing methods refer to standardized procedures developed by ASTM International (formerly known as the American Society for Testing and Materials) for evaluating the physical and mechanical properties of materials. These methods ensure consistency, reliability, and comparability in testing, which is crucial for industries relying on accurate material performance assessments, such as soft robotics, where strain sensors may be used to monitor deformation and performance under various conditions.
Conductive Polymers: Conductive polymers are organic polymers that possess electrical conductivity, allowing them to be used in various electronic applications. These materials can be engineered to exhibit flexibility and stretchability, making them ideal for use in soft robotics and wearable devices. Their unique properties enable their integration into a wide range of sensors and devices, enhancing functionality and performance in fields like biosensing and flexible electronics.
Data Acquisition: Data acquisition refers to the process of collecting, measuring, and analyzing data from various sources in order to monitor and control systems. This process is essential in applications that involve sensors, as it allows for the gathering of real-time information about physical phenomena. By utilizing appropriate sensors and interfaces, data acquisition enables the interpretation of data that informs decision-making and enhances functionality across diverse fields, including robotics, environmental monitoring, and system diagnostics.
Flexible Electronics: Flexible electronics are electronic devices built on bendable substrates, allowing them to be lightweight, thin, and adaptable to various shapes. These characteristics make flexible electronics ideal for a wide range of applications, including sensors that can deform without losing functionality, wearable technology that conforms to the body, and environmental monitoring devices that can be integrated into different surfaces.
Gauge factor: The gauge factor is a numerical value that quantifies the sensitivity of a resistive strain sensor to mechanical deformation. It is defined as the ratio of relative change in electrical resistance to the relative change in length or strain experienced by the material. A higher gauge factor indicates that the sensor will exhibit a larger change in resistance for a given amount of strain, making it an important parameter in designing and selecting strain sensors for various applications.
Hysteresis: Hysteresis refers to the dependence of a system's output on its past states, meaning that the response of the system lags behind the input changes. This lag can lead to different outcomes based on whether a system is being loaded or unloaded, which is particularly important when analyzing materials that exhibit viscoelastic behavior. In contexts like strain sensors, hysteresis is significant as it affects measurement accuracy and the performance of materials under cyclic loading.
ISO Standards for Measurement: ISO standards for measurement refer to a set of internationally recognized guidelines established by the International Organization for Standardization (ISO) that ensure consistency, accuracy, and reliability in various measurement practices across industries. These standards are crucial as they provide a framework for developing and testing measurement tools, including resistive strain sensors, ensuring they meet specific performance criteria and can be compared globally.
Linearization: Linearization is the process of approximating a nonlinear function by a linear function at a specific point, making it easier to analyze and control systems. This technique is particularly useful in simplifying complex mathematical models and facilitating the application of various control strategies, allowing for better predictions and adjustments in system behavior.
Metal foil strain gauges: Metal foil strain gauges are thin, flexible sensors that measure the strain or deformation of an object when subjected to external forces. They consist of a metallic foil pattern that changes its electrical resistance when stretched or compressed, allowing for precise monitoring of structural integrity and mechanical properties. These gauges are widely used in various applications, including load cells and structural health monitoring due to their high accuracy and sensitivity.
Metallic alloys: Metallic alloys are materials created by combining two or more metallic elements, resulting in enhanced properties compared to the individual metals. Alloys can improve strength, ductility, corrosion resistance, and other attributes, making them essential in various applications, including resistive strain sensors. The unique combinations of metals in alloys can lead to specific electrical and mechanical characteristics that are advantageous for sensing applications.
Piezo-resistive sensors: Piezo-resistive sensors are devices that measure changes in resistance due to mechanical deformation or stress, leveraging the piezo-resistive effect, which is the change in electrical resistance when a material is subjected to stress. This characteristic makes them particularly useful for applications where measuring strain or pressure is critical, as they can provide precise and responsive data by converting mechanical changes into electrical signals.
Resistance Change: Resistance change refers to the variation in electrical resistance that occurs in materials, particularly in response to mechanical deformation or strain. This change in resistance is crucial for measuring and detecting stress, enabling the functionality of resistive strain sensors that convert mechanical displacement into an electrical signal. The relationship between applied force and resistance change is often described by the gauge factor, which quantifies how sensitive a resistive sensor is to strain.
Robotic actuation feedback: Robotic actuation feedback refers to the information that is collected from sensors within a robotic system to monitor and control the movement and performance of actuators. This feedback loop is crucial for ensuring precision and accuracy in robotic movements, allowing for adjustments based on real-time data to enhance overall functionality. It is essential in optimizing performance and improving the interaction between the robot and its environment, especially when incorporating resistive strain sensors that detect deformations in materials.
Signal Conditioning: Signal conditioning refers to the process of manipulating a signal to make it suitable for processing and analysis. This involves tasks like filtering, amplifying, and converting signals from sensors into a more usable form, which is crucial in the context of various sensor technologies. Effective signal conditioning enhances the accuracy and reliability of measurements by reducing noise and compensating for signal loss, ensuring that the data generated is meaningful and actionable.
Strain Gauge Working Principle: The strain gauge working principle is based on the concept that the electrical resistance of a conductor changes when it is stretched or compressed. This change in resistance is directly proportional to the amount of strain experienced by the conductor, which allows for precise measurement of deformation. This principle is fundamental to resistive strain sensors, which are used in various applications to monitor stress, load, and structural integrity.
Structural Health Monitoring: Structural health monitoring refers to the process of implementing a damage detection strategy for engineering structures, using various sensors and technologies to assess their condition over time. This involves gathering data on structural responses to loads, environmental conditions, and other factors to ensure safety and longevity. Effective monitoring can prevent failures by enabling proactive maintenance and informing design improvements.
Temperature Coefficient: The temperature coefficient is a numerical value that represents the change in a physical property of a material, such as resistance, per degree of temperature change. In the context of resistive strain sensors, this coefficient is crucial because it helps predict how a sensor's resistance will vary with temperature fluctuations, ensuring accurate strain measurements under different thermal conditions.