Remote characterisation of the environment during physical robot-environment interaction is an important task commonly accomplished in telerobotics. This paper demonstrates how tactile and proximity sensing can be efficiently used to perform automatic crack detection. A custom-designed integrated tactile and proximity sensor is implemented. It measures the deformation of its body when interacting with the physical environment and distance to the environment's objects with the help of fibre optics. This sensor was used to slide across different surfaces and the data recorded during the experiments was used to detect and classify cracks, bumps and undulations. The proposed method uses machine learning techniques (mean absolute value as feature and random forest as classifier) to detect cracks and determine their width. An average crack detection accuracy of 86.46% and width classification accuracy of 57.30% is achieved. Kruskal-Wallis results (p<; 0.001) indicate statistically significant differences among results obtained when analysing only force data, only proximity data and both force and proximity data. In contrast to previous techniques, which mainly rely on visual modality, the proposed approach based on optical fibres is suitable for operation in extreme environments, such as nuclear facilities in which nuclear radiation may damage the electronic components of video cameras.

Proximity and distance estimation sensors are broadly used in robotic hands to enhance the quality of grasping during grasp planning, grasp correction and in-hand manipulation. This paper presents a fiber optical proximity sensor that is integrated with a tactile sensing fingertip of a robotic hand of a mobile robot. The distance estimation of proximity sensors are typically influenced by the reflective properties of an object, such as color or surface roughness. With the approach proposed in this paper, the accuracy of the proximity sensor is enhanced using the information collected by the vision system of the robot. A camera is employed to obtain RGB values of the object to be grasped. Further on, the data obtained from the camera is used to obtain the correct calibration for the proximity sensor. Based on the experimental evidence, it is shown that our approach can be effectively used to reduce the distance estimation error.

It is well known that tactile information can be used to enhance the quality of grasping. Therefore, new technological solutions for sensing in grasping are needed. This paper presents an optical based fingertip sensor that measures both interaction forces and proximity between fingertip and environment. The combination of multiple sensing modalities in the tip of a finger can significantly improve grasping and manipulation capabilities. In this work we present the design and the required calibration of individual sensing elements, and of the integrated fingertip sensor developed for a 3-fingered metamorphic robotic hand. Emulated grasping experiments, using a pinch grip, were performed to illustrate the concept and validate the performance of the developed sensing system. As a result, it was possible to determine the sensor position with respect to an object during approach, contact and grasp.

Current surgical tele-manipulators do not provide explicit haptic feedback during soft tissue palpation. Haptic information could improve the clinical outcomes significantly and help to detect hard inclusions within soft-tissue organs indicating potential abnormalities. However, system instability is often caught by direct force feedback. In this paper, a new approach to intra-operative tumor localization is introduced. A virtual-environment tissue model is created based on the reconstructed surface of a soft-tissue organ using a Kinect depth sensor and the organ's stiffness distribution acquired during rolling indentation measurements. Palpation applied to this tissue model is haptically fed back to the user. In contrast to previous work, our method avoids the control issues inherent to systems that provide direct force feedback. We demonstrate the feasibility of this method by evaluating the performance of our tumor localization method on a soft tissue phantom containing buried stiff nodules. Results show that participants can identify the embedded tumors; the proposed method performed nearly as well as manual palpation.

Advanced tactile tools in minimally invasive surgery have become a pressing need in order to reduce time and improve accuracy in localizing potential tissue abnormalities. In this regard, one of the main challenges is to be able to estimate tissue parameters in real time. In palpation, tactile information felt at a given location is identified by the viscoelastic dynamics of the neighboring tissue. Due to this reason the tissue examination behavior and the distribution of viscoelastic parameters in tissue should be considered in conjunction. This paper investigates the salient features of palpation behavior on soft tissue determining the effectiveness of localizing hard nodules. Experimental studies involving human participants, and validation tests using finite element simulations and a tele-manipulator, were carried out. Two distinctive tissue examination strategies in force-velocity modulation for the given properties of target tissue were found. Experimental results suggest that force-velocity modulations during continuous path measurements are playing an important role in the process of mechanical soft tissue examination. These behavioral insights, validated by detailed numerical models and robotic experimentations shed light on future designs of optimal robotic palpation.

Robot-assisted minimal invasive surgery made it possible to improve the quality of surgical procedures and to enhance clinical outcomes. However, the need to palpate soft tissue organs with the aim to localize potential sites of abnormalities in real time has been recognized. For this work, ten subjects were recruited to perform a remote palpation procedure on a silicone phantom utilizing a tele-manipulation setup, to study their behavior when remotely palpating soft tissue. The stiffness values acquired during the remote palpation of a silicone phantom were transferred to the subjects by means of haptic and visual feedback. Participating subjects were asked to detect hard nodules in the silicone tissue using two distinct strategies: a) randomly chosen movements, and b) trajectory pattern, based on manual palpation techniques for clinical breast examination. We have compared relevant parameters, defining patterns observed during manual palpation, with the counterpart patterns occurring during remote palpation. The results show the effectiveness of applying palpation trajectory pattern used during manual soft tissue examination to tele-manipulation palpation.

This paper investigates how a walker could maintain the variability of an arbitrary set of state variables within desired margins while walking on an uncertain soft terrain. The state variables are dynamically related to the visco-elastic impedance parameters of the body on a given set of uncertain soft terrains using internal memory primitives. A rimless wheel, a walker in its simplest form, is used to perform numerical simulations based on analytical dynamic models and hardware experiments to test a novel algorithm. The rimless wheel model is widely used by the legged locomotion research community to understand basic collision and energetics during passive dynamic walking. Very often, variability of punctuated force perturbations across collisions between the legs and the ground cause uncertain steady state dynamics of walking. This leads to the existence of a finite probability that certain state variables can reach unstable regions. Such phenomenon is known as metastability of walking. In this case, we actuate the rimless wheel with a constant torque leaving it to develop any speed profile for a given visco-elastic impedance distribution of the ground and its own vertical visco-elastic impedance that pushes the rimless wheel against the ground. Here we measure the robustness of the novel algorithm by its ability to shift the distribution of collision forces to a safer region in order to minimize the probability of reaching a given critical force threshold. Our analysis shows that the generalization of the variability of walking in different regions of the internal and external visco-elastic impedance spaces can simplify the computational challenges of robust walking on uncertain visco-elastic terrains.