Fingertip Proximity Sensor with Realtime Visual-based Calibration

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

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

Magnetic fields in single late-type giants in the Solar vicinity: How common is magnetic activity on the giant branches?

We present our first results on a new sample containing all single G,K and M giants down to V = 4 mag in the Solar vicinity, suitable for spectropolarimetric (Stokes V) observations with Narval at TBL, France. For detection and measurement of the magnetic field (MF), the Least Squares Deconvolution (LSD) method was applied (Donati et al. 1997) that in the present case enables detection of large-scale MFs even weaker than the solar one (the typical precision of our longitudinal MF measurements is 0.1-0.2 G). The evolutionary status of the stars is determined on the basis of the evolutionary models with rotation (Lagarde et al. 2012; Charbonnel et al., in prep.) and fundamental parameters given by Massarotti et al. (1998). The stars appear to be in the mass range 1-4 M_sun, situated at different evolutionary stages after the Main Sequence (MS), up to the Asymptotic Giant Branch (AGB). The sample contains 45 stars. Up to now, 29 stars are observed (that is about 64 % of the sample), each observed at least twice. For 2 stars in the Hertzsprung gap, one is definitely Zeeman detected. Only 5 G and K giants, situated mainly at the base of the Red Giant Branch (RGB) and in the He-burning phase are detected. Surprisingly, a lot of stars ascending towards the RGB tip and in early AGB phase are detected (8 of 13 observed stars). For all Zeeman detected stars v sin i is redetermined and appears in the interval 2-3 km/s, but few giants with MF possess larger v sin i.Comment: 4 pages, 3 figures, Proceedings IAU Symposium No. 302, 201

Automatic Fracture Characterization Using Tactile and Proximity Optical Sensing

This paper demonstrates how tactile and proximity sensing can be used to perform automatic mechanical fractures detection (surface cracks). For this purpose, a custom-designed integrated tactile and proximity sensor has been implemented. With the help of fiber optics, the sensor measures the deformation of its body, when interacting with the physical environment, and the distance to the environment's objects. This sensor slides across different surfaces and records data which are then analyzed to detect and classify fractures and other mechanical features. The proposed method implements machine learning techniques (handcrafted features, and state of the art classification algorithms). An average crack detection accuracy of ~94% and width classification accuracy of ~80% is achieved. Kruskal-Wallis results (p < 0.001) indicate statistically significant differences among results obtained when analysing only integrated deformation measurements, only proximity measurements and both deformation and proximity data. A real-time classification method has been implemented for online classification of explored surfaces. In contrast to previous techniques, which mainly rely on visual modality, the proposed approach based on optical fibers might be more suitable for operation in extreme environments (such as nuclear facilities) where radiation may damage electronic components of commonly employed sensing devices, such as standard force sensors based on strain gauges and video cameras

Autonomous Object Handover Using Wrist Tactile Information

Grasping in an uncertain environment is a topic of great interest in robotics. In this paper we focus on the challenge of object handover capable of coping with a wide range of different and unspecified objects. Handover is the action of object passing an object from one agent to another. In this work handover is performed from human to robot. We present a robust method that relies only on the force information from the wrist and does not use any vision and tactile information from the fingers. By analyzing readings from a wrist force sensor, models of tactile response for receiving and releasing an object were identified and tested during validation experiments

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

Method for phase boundary structure control of laminated materials; destruction process investigations of nanostructured coatings with predetermined phase boundary texture

New surface texturing method by means of microplasma coating deposition with the following etching of the coating was shown and described. The method of step by step microplasma texturing was proposed to control the phase boundary of laminated materials. Micrographs of nanostructured inorganic non-metallic coating surface were obtained and analyzed before and after mechanical deformation. The nature of cracks formation and growth was investigated