# Compensating Uncertainties in Force Sensing for Robotic-Assisted Palpation
## 1 Introduction  
More recently, the robotic-assisted minimally invasive surgery (RMIS) has been introduced into the operating room with significant advantages such as improved accuracy, intuitive manipulation, small/invisible incisions and enhanced visualizations etc., as can be witnessed in quite a number of literatures [1; 2; 3; 4]. However, the current RMIS cannot provide proper force/tactile feedback, thus challenges operations such as the cancer tumor removal procedure, in which tumor palpation is usually necessary to locate the tumor area [5]. By directly sensing the stiffness characteristics using hand-held rigid instruments, surgeons can localize the tumor during open surgery. But in RMIS, it is still an unsolved issue for robots to detect the tumor through sensing technique, data acquisition, and processing etc. In [6; 7], detailed surveys of tactile and force sensing devices for robotic and biomedical applications have been presented respectively. To benefit the RMIS utilization, the sensors should be designed subject to special requirements as those mentioned in [8; 9; 10], including (a) repeatability, (b) reliability, (c) speed of sensing, (d) response with static and dynamic, (e) size (limited to about 10 mm in diameter for small portinsertion), (f) sterilizable (using at least one commonly used sterilization method), (g) biocompatible or with a protective sheath and (h) low cost, etc. Based on these requirements, some tactile and force sensors have been developed as presented in [11; 12; 13; 14; 15; 16]. Motivated to achieve tumor localization in RMIS with a tactile or force sensor, considerable efforts have been made as shown in the literatures: In [17] a haptic palpation probe is designed to locate the subcutaneous blood vessel in RMIS. This probe design reduces the cost, and makes the palpation probe disposable. Sliding indentation experiments on a silicone tissue phantom has demonstrated its efficiency. Sliding indentation is one of the palpation methods which makes the probe press a tissue with pre-defined depth and then slides the probe to palpate the tissue. The contact force measured by the sensor can be used to calculate the mechanical property of the tissue. In [18], a novel robotic sweeping palpation method is proposed which is inspired by the actual finger motion during manual palpation in a digital rectal examination (DRE). In [19] a lateral exploration strategy for the classification of inclusions and surrounding tissue is proposed. The above-mentioned methods measure the mechanical property of soft tissue, and detect the hard inclusions from the normal surrounding soft tissue, in which the force information performs the main factor to be sensed during the palpation task. It should be pointed out that the applied force during palpation should be thresholded to a certain limit, as if too large a force is applied to the soft tissue, safety problems may arise. The average maximum force applied by surgeons when manually palpating soft tissue was proved to be around 4.4N from the in vivo experiments in [20]. Furthermore, in [21] it is also mentioned that autonomous robot palpation can reduce the maximum applied force on the soft tissue by more than 35% compared to manual palpation with similar tools. In view of the advantage of autonomous robotic palpation, [22] analyzed the force modulation strategies for robotic palpation to identify the hard region in soft tissue through a learning from demonstration (LfD) based method. Moreover, in [23] presented a remote palpation using a machine learning approach and research in [24] illustrated an autonomous surface recognition using vibration signals. To quantitatively evaluate the mechanical property of soft tissue, the perceived stiffness value is usually used.