Start by testing the tactile sensor's accuracy under real contact conditions
The first thing to test is whether the tactile sensor can measure force accurately when it's actually touching a deformable object—because deformation can distort the sensor itself. A 2024 study built a stretchable glove with 1,152 force-sensing channels and found that without correction, strain from contact caused errors; they used an active suppression method to achieve 97.6% accuracy in force measurement, a 45.3% improvement over uncorrected readings [1]. That means if you skip this step, your system might think it's applying 2 Newtons when it's really applying 3—dangerous for human contact. So before any interaction, run a calibration test that mimics the exact deformable contact you expect, and measure force error with and without strain compensation.
Then verify the system can control force and estimate contact reliably
Once the sensor is accurate, test whether the control loop can maintain a desired force and correctly estimate the contact angle—both critical for safe interaction. A 2023 study used a biomimetic tactile sensor (GTac) to control a tool on deformable objects and demonstrated accurate contact-angle estimation and strong force-tracking robustness [5]. They used a Koopman-based controller to handle the nonlinear dynamics of deformable objects, which is a good reminder that standard linear controllers may not suffice. In practice, this means running a test where the system must apply a constant force to a soft object (like a sponge or a dummy limb) while the object's shape changes, and checking that the force stays within a safe tolerance and the contact angle is correctly identified.
Finally, stress-test generalization to unseen objects, forces, and dynamic conditions
The hardest part is ensuring the system works when conditions change—new objects, unexpected forces, or moving loads. A 2025 study proposed a unified representation (Shape-Space Deformer) that improves generalization to unseen forces and adapts to novel objects, outperforming existing methods in reconstruction accuracy and robustness [3]. Another 2026 study deliberately used a shifting liquid in a soft cup to stress-test a visuo-tactile reflex controller, because the continuously changing load leaves no static operating point—a worst-case scenario for force control [4]. These studies agree that generalization is the key bottleneck: test with objects and force profiles you didn't train on, and include dynamic disturbances. If the system fails there, it's not ready for people.
About These Sources
This answer is built on 5 peer-reviewed studies — published from 2023 to 2026, 3 from 2024 or later, 1 in Q1 journals — selected as the most relevant from 5 studies that passed quality screening, drawn from 37 papers retrieved from a database of over 500 million.
Sources used in this answer
Capturing forceful interaction with deformable objects using a deep learning-powered stretchable tactile array
A 2024 study with a 1,152-channel stretchable tactile glove achieved 97.6% force-measurement accuracy using an active strain-suppression method, a 45.3% improvement over uncorrected readings, and reconstructed hand-object states with an average error of 1.8 cm across 24 objects.
Visuo-Tactile Feedback-Based Robot Manipulation for Object Packing
A 2023 study on object packing showed that a visuo-tactile feedback framework (combining vision, tactile, and force/torque) outperformed existing methods in accuracy and efficiency, using deep reinforcement learning to select optimal actions.
Shape-Space Deformer: Unified Visuo-Tactile Representations for Robotic Manipulation of Deformable Objects
A 2025 study proposed Shape-Space Deformer, a unified representation for deformable object reconstruction that improved generalization to unseen forces and rapid adaptation to novel objects, with significant gains in reconstruction accuracy and robustness, suitable for real-time use.
TactileReflex: Noise-Statistics-Driven Vision-Tactile Reflex Control for Force-Sensitive Manipulation
A 2026 study on TactileReflex used a shifting liquid in a soft cup to stress-test visuo-tactile reflex control, demonstrating the challenge of continuously redistributed loads with no static operating point.
Interaction Control for Tool Manipulation on Deformable Objects Using Tactile Feedback
A 2023 study using the GTac tactile sensor showed that a tactile-guided planning and control framework could accurately estimate contact angle and achieve strong force-tracking robustness on deformable objects, using a Koopman-based optimal controller.