Autonomous Robotic Palpation of Soft Tissue using the Modulation of Applied Force

Palpation or perception of tactile information from soft tissue organs during minimally invasive surgery is required to improve clinical outcomes. One of the methods of palpation includes examination using the modulation of applied force on the localized area. This paper presents a method of soft tissue autonomous palpation based on the mathematical model obtained from human tactile examination data using modulations of palpation force. Using a second order reactive auto-regressive model of applied force, a robotic probe with spherical indenter was controlled to examine silicone tissue phantoms containing artificial nodules. The results show that the autonomous palpation using the model abstracted from human demonstration can be used not only to detect embedded nodules, but also to enhance the stiffness perception compared to the static indentation of the probe

Palpation force modulation strategies to identify hard regions in soft tissue organs

This work was supported by EPSRC MOTION grant (grant number EP/N03211X/1), National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London and Vattikuti Foundation

ESPRESS.0: Eustachian Tube-Inspired Tactile Sensor Exploiting Pneumatics for Range Extension and SenSitivity Tuning

Optimising the sensitivity of a tactile sensor to a specific range of stimuli magnitude usually compromises the sensor’s widespread usage. This paper presents a novel soft tactile sensor capable of dynamically tuning its stiffness for enhanced sensitivity across a range of applied forces, taking inspiration from the Eustachian tube in the mammalian ear. The sensor exploits an adjustable pneumatic back pressure to control the effective stiffness of its 20 mm diameter elastomer interface. An internally translocated fluid is coupled to the membrane and optically tracked to measure physical interactions at the interface. The sensor can be actuated by pneumatic pressure to dynamically adjust its stiffness. It is demonstrated to detect forces as small as 0.012 N, and to be sensitive to a difference of 0.006 N in the force range of 35 to 40 N. The sensor is demonstrated to be capable of detecting tactile cues on the surface of objects in the sub-millimetre scale. It is able to adapt its compliance to increase its ability for distinguishing between stimuli with similar stiffnesses (0.181 N/mm difference) over a large range (0.1 to 1.1 N/mm) from only a 0.6 mm deep palpation. The sensor is intended to interact comfortably with skin, and the feasibility of its use in palpating tissue in search of hard inclusions is demonstrated by locating and estimating the size of a synthetic hard node embedded 20 mm deep in a soft silicone sample. The results suggest that the sensor is a good candidate for tactile tasks involving unpredictable or unknown stimuli

A Passive Variable Impedance Control Strategy with Viscoelastic Parameters Estimation of Soft Tissues for Safe Ultrasonography

In the context of telehealth, robotic approaches have proven a valuable solution to in-person visits in remote areas, with decreased costs for patients and infection risks. In particular, in ultrasonography, robots have the potential to reproduce the skills required to acquire high-quality images while reducing the sonographer's physical efforts. In this paper, we address the control of the interaction of the probe with the patient's body, a critical aspect of ensuring safe and effective ultrasonography. We introduce a novel approach based on variable impedance control, allowing real-time optimisation of a compliant controller parameters during ultrasound procedures. This optimisation is formulated as a quadratic programming problem and incorporates physical constraints derived from viscoelastic parameter estimations. Safety and passivity constraints, including an energy tank, are also integrated to minimise potential risks during human-robot interaction. The proposed method's efficacy is demonstrated through experiments on a patient dummy torso, highlighting its potential for achieving safe behaviour and accurate force control during ultrasound procedures, even in cases of contact loss.Comment: 7 pages, 7 figures, submitted to ICRA 202

Soft Morphological Computation

Soft Robotics is a relatively new area of research, where progress in material science has powered the next generation of robots, exhibiting biological-like properties such as soft/elastic tissues, compliance, resilience and more besides. One of the issues when employing soft robotics technologies is the soft nature of the interactions arising between the robot and its environment. These interactions are complex, and the their dynamics are non-linear and hard to capture with known models. In this thesis we argue that complex soft interactions can actually be beneficial to the robot, and give rise to rich stimuli which can be used for the resolution of robot tasks. We further argue that the usefulness of these interactions depends on statistical regularities, or structure, that appear in the stimuli. To this end, robots should appropriately employ their morphology and their actions, to influence the system-environment interactions such that structure can arise in the stimuli. In this thesis we show that learning processes can be used to perform such a task. Following this rationale, this thesis proposes and supports the theory of Soft Morphological Computation (SoMComp), by which a soft robot should appropriately condition, or ‘affect’, the soft interactions to improve the quality of the physical stimuli arising from it. SoMComp is composed of four main principles, i.e.: Soft Proprioception, Soft Sensing, Soft Morphology and Soft Actuation. Each of these principles is explored in the context of haptic object recognition or object handling in soft robots. Finally, this thesis provides an overview of this research and its future directions.AHDB CP17