Tactile sensing refers to a robot’s ability to obtain information about physical interactions through touch, allowing it to monitor and detect contacts on their surfaces. As an instrumental modality of robotic manipulation, tactile sensing provides information that is inaccessible using remote sensors like lidars or cameras.1,2
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In recent years, tactile sensing has emerged as the key technology enabling complex task implementation using robotic systems. Touch is specifically critical in unstructured environments due to the robot’s inaccurate internal representation of manipulated objects.
Robots equipped with tactile sensors could obtain the direction and magnitude of a contact force, humidity, temperature, and texture. Such information is crucial for path planning, obstacle avoidance, and stable grasp in unstructured environments.1,2
The Tactile Sensing Process: An Overview
The robotic tactile sensing process can be divided into functional blocks that portray perception, sensing, and action at various levels. Functional blocks that depict sensing include transduction (multimodal); sensor bias, signal conditioning, and data acquisitions; on-board signal processing, such as linearization and temperature compensation; and tactile data transmission.3
The term perception refers to the object property observing process through sensing. Perception involves sensor fusion/representation and tactile data decoding, such as slip and shape detection and material perception. Tactile sensing array, interface electronics and data acquisition, embedded data processing unit, transmission bus interface, communication bus hierarchy, computing hardware, and controller are primarily used in the tactile sensing process.3
Initially, the sensing process transduces the external stimuli like vibration, pressure, and thermal stimulus into changes in the tactile sensor’s sensing elements. Then, this data is collected, conditioned, and processed by employing an embedded data processing unit, and transferred to the perception level to develop a world model and perceive the interacted objects’ properties, like material properties and shape.3
The sense of touch could be fused with other sensing modalities like auditory and vision perception while perceiving. Eventually, control commands are exerted to realize the desired actions by the controller.3
What are the Different Types of Tactile Sensors?
Various types of tactile sensors, such as piezoelectric, piezoresistive, and capacitive, are typically used in robotics. Each type operates based on different principles, allowing robots to detect forces, pressure, texture, and other physical properties during manipulation tasks.4
Capacitive Sensors
Capacitive sensors operate on a straightforward principle: two electrodes are separated by a dielectric material and supported by an elastic element. For these sensors to provide measurements, they need active excitation and demodulation. Initially, this requirement limited their application in robotics. But everything changed with the rise of touchscreens, which spurred the development of affordable capacitance-to-digital (CTD) integrated circuits and opened the door for wider use.
Today, most modern CTDs use frequency- or time-based techniques, packaging their electronic front-end systems, data acquisition, and excitation circuits into a single chip. While this compact design is efficient, it comes with trade-offs. Many commercial CTDs fall short when it comes to delivering the high signal-to-noise ratio (S/N) needed for precise tactile sensing—typically, an S/N greater than 20 dB is required. On top of that, slow response times remain an issue. Achieving higher S/N levels often means averaging multiple measurement sequences, which can push output rates beyond 1 millisecond.
These challenges highlight the ongoing need to refine capacitive sensors for robotics, especially in scenarios where precision and speed are equally critical.4
Piezo-Electric Sensors
Piezoelectric sensors are widely used as vibration and tactile sensors due to their impressive dynamic response, often exceeding 10 kHz. However, they fall short at low frequencies, providing zero output when exposed to steady pressure. These sensors typically rely on piezo polymers or ceramics, such as polyvinylidene fluoride (PVDF), for tactile sensor applications.
The working principle of piezo materials is straightforward yet remarkable: when subjected to mechanical stress, they generate electric charges. These charges are then collected by conductive electrodes and amplified to produce a voltage, eliminating the need for external electrical excitation—a key advantage for many applications.
Despite their benefits, piezoelectric sensors come with significant design challenges. Their electronic front-end requires amplifiers with low noise and high input impedance, making it difficult to create embedded systems using standard commercial components. Moreover, the tactile system design demands precise geometry to ensure the sensor captures the desired mechanical input. This is particularly important because piezo materials are highly sensitive to various types of mechanical stresses.
While piezoelectric sensors excel in dynamic environments, their limitations and design complexity require careful consideration to optimize performance for specific applications.4
Piezo-Resistive Sensors
Piezo-resistive sensors were among the first technologies adopted for tactile sensing, thanks to their relatively simple yet effective design. They consist of two electrodes connected by a conductive, filler-loaded deformable elastomer. This elastomer is engineered to reach the percolation threshold, enabling significant changes in resistance under mechanical pressure. In their unloaded state, these sensors exhibit very high resistivity, typically exceeding 10 MΩ·cm. When external pressure is applied, the resistance drops dramatically—often to just a few kilohms or less.
To operate, piezo-resistive sensors require a constant driving voltage. Measurements are performed using a voltage divider circuit, which pairs the sensor with a precision reference resistor. However, one notable challenge with these devices is their susceptibility to noise. To mitigate this, special elastomers such as quantum tunneling composites are used, as they exhibit significantly lower noise levels, improving overall sensor performance.
While piezo-resistive sensors have played a foundational role in tactile sensor development, their design and material considerations remain critical to ensuring accurate and reliable performance in various applications.4
The Significance of Robotic Tactile Sensing
Robotic tactile sensing plays a crucial role in enhancing a robot's ability to interact with and understand its environment. It is essential for tasks such as material properties recognition, object shape estimation, and pose estimation.2
Material Properties Recognition
Understanding material properties such as softness, hardness, and roughness is key to effective robotic interaction. By recognizing these traits, robots can adjust their grip strength and ensure a more intuitive engagement with objects. For instance, MEMS-based tactile sensors analyze vibratory patterns during sliding motions to distinguish surface textures, using techniques like Maximum Likelihood Estimation for accuracy.
Robots can also identify materials based on stiffness. Piezoresistive tactile sensors, for example, classify objects by stiffness using algorithms such as k-nearest neighbor (KNN) and dynamic time-warping. These approaches allow robots to reliably differentiate materials, enhancing their ability to handle diverse objects.2
Object Shape Estimation
Understanding material properties such as softness, hardness, and roughness is key to effective robotic interaction. By recognizing these traits, robots can adjust their grip strength and ensure a more intuitive engagement with objects. For instance, MEMS-based tactile sensors analyze vibratory patterns during sliding motions to distinguish surface textures, using techniques like Maximum Likelihood Estimation for accuracy.
Robots can also identify materials based on stiffness. Piezoresistive tactile sensors, for example, classify objects by stiffness using algorithms such as k-nearest neighbor (KNN) and dynamic time-warping. These approaches allow robots to reliably differentiate materials, enhancing their ability to handle diverse objects.2
Object Pose Estimation
Accurately estimating the pose of the in-hand object is essential for dexterous manipulation. Pressure sensors/camera-based tactile sensors could be used for effective object pose estimation.2
Specifically, in-hand object pose could be estimated by matching the principal component analysis-based features obtained from tactile pressure readings to the object’s geometric features. Similarly, a feature-based height map registration method can be used to localize the small objects in camera-based tactile sensor-driven approaches.2
By learning to recognize materials, estimate shapes, and determine object positions, tactile sensing allows robots to interact with the world in ways that feel almost natural. As this technology advances, robots will keep breaking new ground, becoming smarter, more adaptable, and better equipped to handle real-world challenges across a variety of industries.
Challenges and Recent Advances
Despite its growing importance, tactile sensing in robotics still faces significant hurdles. One major challenge is scalability—large sensor arrays are often plagued by crosstalk, wiring complexities, and latency issues. Additionally, most tactile sensing systems rely heavily on reactive control, which limits their ability to actively explore environments the way humans do. Achieving effective multimodal fusion—combining sensory inputs like touch and vision for human-level perception—also remains an open problem.
However, progress is being made. A recent study published in Nature Communications introduced a flexible tactile sensor that uses thin-film thermistors to achieve multimodal perception. This sensor can detect properties such as thermal characteristics, texture, temperature, pressure, and even slippage. Notably, it demonstrated exceptional performance in slip sensing, with an ultrafast response time of 4 ms and the ability to detect slip velocities as low as 0.05 mm/s. These capabilities are crucial for precise and reliable grasping, helping robots avoid dropping slippery objects or damaging delicate ones.
The same study also unveiled a groundbreaking robotic tactile-visual fusion architecture. This system integrates various sensory modalities seamlessly, from the foundational sensory inputs to the highest levels of robotic decision-making. Such advancements mark an exciting step forward in bridging the gap between human and robotic tactile perception.6
Future Outlook
The future of tactile sensing in robotics is incredibly exciting. As sensor technology improves, robots will become much better at handling delicate tasks like manipulating objects and identifying materials. They’ll also be able to navigate messy, unpredictable environments with far greater precision.
Right now, challenges like crosstalk and slow response times in large sensor arrays can hold robots back, but these hurdles are being tackled. With faster, more accurate sensors, robots will gain the finesse they need for more complex tasks. Adding tactile and visual feedback into the mix will make them even smarter—able to "see" and "feel" the world around them in a way that’s closer to how humans do.
These advancements won’t just make robots more capable; they’ll make them genuinely helpful across industries. Whether it’s assembling tiny components, assisting in surgeries, or managing fragile items in a warehouse, tactile sensing will be key to creating robots that are not just machines, but partners in solving real-world problems.
Interested in Learning More About the Future of Tactile Robotics?
Tactile robotics is changing the game, bringing a new level of precision and adaptability to industries everywhere. The future of robotics is tactile, and it’s closer than you think.
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References and Further Reading
- Gomes, D. F., Luo, S. (2022). Geltip tactile sensor for dexterous manipulation in clutter. Tactile Sensing, Skill Learning, and Robotic Dexterous Manipulation, 3-21. DOI: 10.1016/B978-0-32-390445-2.00008-8, https://www.sciencedirect.com/science/article/abs/pii/B9780323904452000088
- Jiang, J., Luo, S. (2022). Robotic perception of object properties using tactile sensing. Tactile Sensing, Skill Learning, and Robotic Dexterous Manipulation, 23-44. DOI: 10.1016/B978-0-32-390445-2.00009-X, https://www.sciencedirect.com/science/article/abs/pii/B978032390445200009X
- Luo, S., Bimbo, J., Dahiya, R., Liu, H. (2017). Robotic tactile perception of object properties: A review. Mechatronics, 48, 54-67. DOI: 10.1016/j.mechatronics.2017.11.002, https://www.sciencedirect.com/science/article/abs/pii/S0957415817301575
- Natale, L., Cannata, G. (2021). Tactile Sensing. ArXiv. DOI: 10.1007/978-94-007-7194-9_110-1, https://arxiv.org/abs/2105.05089
- Mandil, W., Rajendran, V., Nazari, K. (2023). Tactile-Sensing Technologies: Trends, Challenges and Outlook in Agri-Food Manipulation. Sensors, 23(17), 7362. DOI: 10.3390/s23177362, https://www.mdpi.com/1424-8220/23/17/7362
- Mao, Q., Liao, Z., Yuan, J., Zhu, R. (2024). Multimodal tactile sensing fused with vision for dexterous robotic housekeeping. Nature Communications, 15(1), 1-12. DOI: 10.1038/s41467-024-51261-5, https://www.nature.com/articles/s41467-024-51261-5
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