TY - JOUR A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Optimisation of Prehension Force through Tactile Sensing JF - Industrial Robot N2 - Purpose The purpose of this paper is to analyze surface deformations caused by shear and moment forces on tactile materials and present a method to detect and reduce the risk of slippage by controlling the normal force as measured by tactile sensor arrays. Design/methodology/approach A predictive model has been proposed which uses a basic method adapted to real applications in grasp optimization. Prevention of premature release with minimum prehension force is addressed without the need to measure the coefficient of friction between object and robot gripper. Predictive models have been used to develop a set of rules which predict the pre‐slip based on fluctuations in tactile signal data. Findings The tactile sensors can be used in a “nonlinear” manner during manipulation tasks. When the gripper finger first makes contact with an object, the stress distribution under the finger skin varies rapidly. Predictive models have been used to develop a set of rules which predict the pre‐slip based on fluctuations in tactile signal data. Pre‐slip at the contact area just prior to object movement produces rapid but detectable stress transients. Originality/value Tactile sensors do not measure stress generated by a contact with an object directly, but instead measure strain in an interposed compliant, polymeric medium intended for sensor protection and prehension assistance. Reliable detection of pre‐slip has hitherto eluded researchers using such tactile techniques. KW - Sensors KW - Tactile sensors Y1 - 2008 U6 - https://doi.org/10.1108/01439910810876454 VL - 35 IS - 4 SP - 361 EP - 368 PB - MCB Univ. Press CY - Bradford ER - TY - CHAP A1 - Petchartee, Somrak A1 - Monkman, Gareth J. A1 - Suebsromran, Anan ED - Mukhopadhyay, S.C. ED - Gupta, G.S. T1 - 3D-Shape Recognition based Tactile Sensor T2 - Smart Sensors and Sensing Technology N2 - A surface recognition algorithm capable of determining contact surfaces types by means of tactile sensor fusion is proposed. The authors present a recognition processes for 3-dimensional deformations in a 2-dimensional parametric domain. Tactile information is extracted by physical contact with a grasped object through a sensing medium. Information is obtained directly at the interface between the object and the sensing device and relates to three-dimensional position and orientation of the object in the presence of noise. The technique called “eigenvalue trajectory analysis”, is introduced and adopted for specifying the margin of classification and classification thresholds. The authors demonstrate mathematically that this approach, which complements existing work, offers significant computational advantages when applied to challenging contact scenarios such as dynamic recognition of contact deformations. Y1 - 2008 SN - 978-3-540-79589-6 SN - 978-3-540-79590-2 U6 - https://doi.org/10.1007/978-3-540-79590-2_21 SP - 317 EP - 332 PB - Springer CY - Berlin ; Heidelberg ER - TY - CHAP A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - 3D-Shape Recognition based Tactile Sensor T2 - ICST 2007, Proceedings of 2nd International Conference on Sensing Technology : Massey University, Palmerston North, New Zealand, November 26 - 28, 2007 Y1 - 2007 SP - 56 EP - 61 PB - Inst. of Information Sciences and Techn., Massey Univ. CY - Palmerston ER - TY - JOUR A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Pre-slip Sensing through Tactile Sensing JF - Sensors & Transducers Y1 - 2008 UR - https://www.sensorsportal.com/HTML/DIGEST/P_SI_48.htm SN - 1726-5479 VL - 90 IS - 4, Special Issue SP - 310 EP - 324 PB - International Frequency Sensor Association (IFSA) ER - TY - CHAP A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Contact Identification using Tactile Arrays T2 - Proceedings of the 7th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2007), 15.-18.12.2007, Giza, Egypt N2 - The proposed method allows a robot to quantify tactile recognition of grasped objects. The responses by the robot are matched by randomly introducing objects following the completion of tactile sensor based training phases on 4 specific objects. The reproduction of the robotic contact identification is accomplished by matching threshold values of the smallest eigenvalue of the Quadric surface - called the eigenvalue trajectory. Once the grasped objects are introduced to the 2-fingered robot hand, the eigenvalue trajectory of contact surfaces are calculated by the system. Calculations are based on the degree of similarity of the characteristics between the newly received and previously trained tactile data. Experimental results indicate that the proposed algorithm allows a successful quantification of robotic contact recognition and the accomplishment of high levels of accuracy in contact identification. These results confirm that the proposed method is useful for identifying contact surfaces based on tactile sensor data. KW - Touch recognition KW - contact classification KW - tactile sensor Y1 - 2007 U6 - https://doi.org/10.1109/ISSPIT.2007.4458144 SP - 1121 EP - 1126 PB - IEEE ER - TY - CHAP A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Contact Classification using Tactile Arrays T2 - 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information (ISSNIP), 3, 03.-06.12.2007, Melbourne, VIC, Australia N2 - This paper proposed a contact recognition algorithm capable of determining contact surfaces types by tactile sensor fusion. This algorithm can recognize grasped objects using a 2- fingered robot hand, on which tactile sensors are mounted. Experiments have demonstrated reliable surface classification and accurate transformation independent of object shape and orientation. The contribution of this paper regards the relations between a surface and the points cloud defining it. Particularly, we investigate on the possibility that there is some intrinsic feature of a points cloud under quadric surface, allowing us to discriminate or classify a dataset defining a surface from the acquisition noise. KW - manipulators KW - objec recognition KW - sensor arrays KW - signal classification KW - tactile sensors Y1 - 2007 U6 - https://doi.org/10.1109/ISSNIP.2007.4496848 SP - 227 EP - 232 ER - TY - JOUR A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Contact Recognition using Tactile Sensor JF - Annals Universitaria Craiova-Series: Automation, Computers, Electronics and Mechatronics N2 - The surface recognition algorithm that determines the types of contact surfacesby fusing information collected by the tactile sensor system is proposed. The tactilesystem will be determined from the shape of the object image which can then becharacterized using the mathematical properties of Quadric surface. This algorithm canrecognize 3-D objects using a 2-fingered robot gripper, on which tactile sensors aremounted. Experiments have demonstrated the reliability of the surface classificationmethod and the accuracy of transformations independent of an object’s shape, translationand rotation. Y1 - 2007 UR - https://www.academia.edu/1204885/CONTACT_RECOGNITION_USING_TACTILE_SENSOR VL - 4 (31) IS - 2 SP - 103 EP - 108 ER - TY - JOUR A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Optimisation of Prehension Force through Tactile Sensing JF - Journal of Advanced Manufacturing Technology Y1 - 2007 SN - 2289-8107 PB - Universiti Teknikal Malaysia Melaka ER - TY - JOUR A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Contact Recognition through Tactile Sensing JF - ACTA Universitatis Apulensis; Seria Mathematics-Informatics Y1 - 2007 SN - 1582-5329 PB - Department of Mathematics and Informatics CY - Alba Iulia ER - TY - CHAP A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Contact Recognition using Tactile Sensor T2 - Proc. International Symposium on System Theory, Automation, Robotics, Computers, Informatics, Electronics and Instrumentation (SINTES13), Romania Y1 - 2007 SP - 285 EP - 290 ER - TY - CHAP A1 - Petchartee, Somrak A1 - Monkman, Gareth J. T1 - Pre-slip detection based Tactile Sensing T2 - Proc. 3rd International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007), Melbourne Y1 - 2007 SP - 233 EP - 238 ER -