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Page 14 of 26 Jin et al. Soft Sci 2023;3:8 https://dx.doi.org/10.20517/ss.2022.34

Internal properties recognition
Internal properties describe the object inner parameters, which provide a more complete view of the
anisotropic target [Figure 7D]. Traditionally, internal damage such as micro holes or cracks can be detected
through acoustic and infrared devices, the principles of which are always based on excitation and echo
signals . Most haptic devices aim to extract object external properties, and robotic tactile sensors for
[72]
internal properties measurement are less reported. Before then, researchers measured the liquid content by
shaking or rolling the container, and the vibration or multi-axis force signals were further processed
[141]
through GP or high pass filter (HPF) . Others differentiated the inner-outer shape of the objects
[150]
covered with soft materials with visual and tactile data .
[142]
Robotic grasping and manipulation
With the development of robotic technology and industrial demands, robots are more expected to work in
unstructured environments, which calls for strong environmental adaptability and complicated task
processing capacity. It is promising for robotics, the multi-finger manipulators or graspers, to conduct high-
level and complicated manipulation tasks such as stable grasping, dexterous operation, or even tool
manipulation. This section discusses the grasping stability enhancement methods and some dexterous
operating applications in robotics.

Stability control of robotic grasping
Grasping is one of the most fundamental and widely used operation movements for robotics, especially in
the multi-finger manipulator or grasper . It provides robots with the ability for object transferring and
[151]
recognition, and it is also a premise of some non-grasp or tool manipulation tasks. The complete grasping
[17]
process can be divided into pre-grasping, grasp conducting and grasp verification . To perform dexterous
and sophisticated manipulation tasks, it is of great significance to improve grasping stability, and commonly
used methods for stable grasp include pose adaptation or adjustment, force control, and slippage detection.

The grasp adaption and adjustment is an important stability control method at the beginning of the
grasping tasks. The primary purpose of this adjustment is to search for a proper grasping position or
relocate the grasped target . In the stage of pre-grasping, researchers can use vision or proximity sensors to
[6]
roughly estimate the object shape and pose [152,153] , which assists in choosing a proper grasping gesture that
matches the target object, and an initial grasping position is estimated to reduce the torsional load to the
grasping manipulator. Then tentative grasping is conducted and the object pose and inertial parameters are
revised through tactile information, which can further adjust the grasping gesture and minimize torsional
[140]
load . If the initially estimated grasping is far from the expected state, it is necessary to conduct re-
grasping. Otherwise, the manipulator can quickly perform an in-hand operation based on the current
grasping state, which relies on the manipulator’s dexterity and operating skills.

Once choosing a proper grasping gesture and position, it should give priority to considering force feedback
[52]
and controlling for stable grasping . First, the appropriate measurement of the object weight helps estimate
the minimum grasping force, which ensures the probable lifting of the target object. Moreover, it is
[146]
necessary to determine the maximum grasping force by estimating the object stiffness , which can prevent
[146]
damage or a tight grip on the object with delicate or soft materials. Qiu et al. [Figure 8A] have reported a
robotic hand integrated with bioinspired multisensory electronic skins. The comparative result indicates
that the manipulator with force feedback can grasp tomato stably, while the one without force monitoring
results in damage. Others have applied force feedback to a prosthetic hand , which assists disabled people
[20]
in interacting with fragile or soft objects.