A Pretouch Sensing System for a Robot Grasper Using Magnetic and Capacitive Sensors

Pretouch sensors are capable to classify objects and estimate their position prior to touching and thus close the gap between vision- and contact-based sensing. This will be particularly useful for robotics applications not only just for manipulation of objects but also with respect to safety. As robots will more and more operate in “open environments” where there is little prior knowledge, it will be important to gather as much information on the environment as possible. However, although there are many measurement principles that might be applied, only a few can cope with the requirements, e.g., limitations with respect to spatial dimensions, weight, and power consumption. In this paper, we investigate a measurement system for two types of materials. Dielectric and ferromagnetic materials, which are common in many industrial applications, can be located and distinguished in the vicinity of a robot grasper. Inspired by magnetic field tomography, we use a permanent magnet and apply giant magnetic resistor sensors to measure the magnetic field deformation caused by ferromagnetic objects. Furthermore, we use an electrical capacitance tomography approach to measure the change of the electric field by dielectric objects. Based on the measurement results, we solve an inverse problem with respect to the object position and spatial permittivity distribution. We present experimental results for a prototype implementation and provide a description of the calibration method.

[1]  Bernhard Brandstätter,et al.  Inverse problems, Ill-posedness and regularization – an illustrative example , 2007, Elektrotech. Informationstechnik.

[2]  Larry K. Baxter,et al.  Capacitive Sensors: Design and Applications , 1996 .

[3]  Ashutosh Saxena,et al.  Reactive grasping using optical proximity sensors , 2009, 2009 IEEE International Conference on Robotics and Automation.

[4]  Robert X. Gao,et al.  Enhancement of Measurement Efficiency for Electrical Capacitance Tomography , 2011, IEEE Transactions on Instrumentation and Measurement.

[5]  Joshua R. Smith,et al.  Seashell effect pretouch sensing for robotic grasping , 2012, 2012 IEEE International Conference on Robotics and Automation.

[6]  R. Fletcher Practical Methods of Optimization , 1988 .

[7]  Christian Magele,et al.  Hidden metallic object localization by using giant magnetic resistor sensors , 2011 .

[8]  Phaneendra K. Yalavarthy,et al.  Helmholtz-Type Regularization Method for Permittivity Reconstruction Using Experimental Phantom Data of Electrical Capacitance Tomography , 2010, IEEE Transactions on Instrumentation and Measurement.

[9]  M. Neumayer,et al.  Electrical Capacitance Tomography: Current sensors/algorithms and future advances , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[10]  Christopher K. I. Williams,et al.  Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) , 2005 .

[11]  John T. Feddema,et al.  Whole arm obstacle avoidance for teleoperated robots , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[12]  Brian Mayton,et al.  Electric Field Pretouch : Towards Mobile Manipulation , 2009 .

[13]  Stoyan N. Nihtianov,et al.  Power-Efficient High-Speed and High-Resolution Capacitive-Sensor Interface for Subnanometer Displacement Measurements , 2012, IEEE Transactions on Instrumentation and Measurement.

[14]  Daniel Watzenig,et al.  Reconstruction of inhomogeneities in fluids by means of capacitance tomography , 2003 .

[15]  Stavros Chatzandroulis,et al.  A Reconfigurable Multichannel Capacitive Sensor Array Interface , 2011, IEEE Transactions on Instrumentation and Measurement.

[16]  S. Nihtianov,et al.  Comparison of different methods to cancel offset capacitance in capacitive displacement sensors , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[17]  N. Karlsson Theory and application of a capacitive sensor for safeguarding in industry , 1994, Conference Proceedings. 10th Anniversary. IMTC/94. Advanced Technologies in I & M. 1994 IEEE Instrumentation and Measurement Technolgy Conference (Cat. No.94CH3424-9).

[18]  Wuqiang Yang,et al.  Prior-online iteration for image reconstruction with electrical capacitance tomography , 2004 .

[19]  M. Neumayer,et al.  Current Reconstruction Algorithms in Electrical Capacitance Tomography , 2011 .

[20]  C. Fox,et al.  Accelerated Markov chain Monte Carlo sampling in electrical capacitance tomography , 2011 .

[21]  Jiamin Ye,et al.  Evaluation of Effect of Number of Electrodes in ECT Sensors on Image Quality , 2012, IEEE Sensors Journal.

[22]  H.-C. Kim,et al.  Electrical impedance tomography reconstruction algorithm using extended Kalman filter , 2001, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570).

[23]  Sailes K. Sengijpta Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[24]  Boby George,et al.  Seat Occupancy Detection Based on Capacitive Sensing , 2009, IEEE Transactions on Instrumentation and Measurement.

[25]  R. Fletcher,et al.  Practical Methods of Optimization: Fletcher/Practical Methods of Optimization , 2000 .

[26]  Joshua R. Smith,et al.  Electric field imaging pretouch for robotic graspers , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[27]  H. Zangl,et al.  A GMR based magnetic pretouch sensing system for a robot grasper , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.