Design and characterization of an instrumented hand-held power tool to capture dynamic interaction with the workpiece during manual operations

In recent years, robots have contributed extensively to the automation of repetitive tasks for which position control-based approaches represent effective solutions. However, other contact tasks such as finishing, deburring and grinding require both position and force control. To date, despite the availability of cost-effective robotic solutions, such tasks are still carried out manually by skilled operators mainly because programming is time consuming and not sufficiently flexible to be readapted to product or task changes. An alternative approach is teaching by demonstration, by instrumenting hand-held tools for capturing both the force and the contact point while an expert operator performs tooling tasks. This paper presents a novel approach for instrumenting hand-held tools for polishing/grinding used in monitoring the performance of skilled human operators which can be, in future work, translated into planning strategies for robot programming and control. More specifically, the instrumented tool is designed to monitor interaction forces with the workpiece and point of contact, where these interaction forces arise. The key element in our design is a flexible coupler which, ideally, only transmits rotation torques to spin the polishing/grinding wheel while all the remaining torque and force components are transmitted through a parallel structure and sensed by a 6-axis loadcell. Sensing torques, in addition to forces, also allows for a dynamic estimation of the point of contact.

[1]  Haobo Cheng,et al.  An investigation of the effects of the tool path on the removal of material in polishing , 2010 .

[2]  Paolo Tommasino,et al.  Geometry of contact during tooling tasks via dynamic estimation , 2018 .

[3]  Domenico Campolo,et al.  Characterization of impedance rendering with a cable-driven agonist-antagonist haptic device , 2014, 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV).

[4]  Soichi Ibaraki,et al.  MONITORING OF CUTTING FORCE USING SPINDLE DISPLACEMENT SENSOR , 2004 .

[5]  Vijay Kumar,et al.  Control and Coordination of Multiple Mobile Robots in Manipulation and Material Handling Tasks , 1999, ISER.

[6]  Jongwon Kim,et al.  Real-Time Tool Breakage Monitoring for NC Milling Process , 1995 .

[7]  W. K. Teo,et al.  Programming a Robot for Conformance Grinding of Complex Shapes by Capturing the Tacit Knowledge of a Skilled Operator , 2017, IEEE Transactions on Automation Science and Engineering.

[8]  A Fiorito,et al.  Bone and joint disorders in the upper extremities of chipping and grinding operators , 1987, International archives of occupational and environmental health.

[9]  Stephen P. Radzevich Kinematic geometry of surface machining , 2007 .

[10]  K. H. Hunt,et al.  Kinematic geometry of mechanisms , 1978 .

[11]  Carme Torras,et al.  Learning Physical Collaborative Robot Behaviors From Human Demonstrations , 2016, IEEE Transactions on Robotics.

[12]  Ichiro Inasaki,et al.  Development of a Magnetostrictive Torque Sensor for Milling Process Monitoring , 1997, Manufacturing Science and Engineering: Volume 1.

[13]  Yusuf Altintas,et al.  Prediction of Cutting Forces and Tool Breakage in Milling from Feed Drive Current Measurements , 1992 .

[14]  R Letz,et al.  A cross sectional epidemiological survey of shipyard workers exposed to hand-arm vibration. , 1992, British journal of industrial medicine.

[15]  Alessandro Gasparetto,et al.  Automatic Path and Trajectory Planning for Robotic Spray Painting , 2012, ROBOTIK.

[16]  G. Tolstov Fourier Series , 1962 .

[17]  Etienne Burdet,et al.  Estimating Human Wrist Stiffness during a Tooling Task , 2020, Sensors.

[18]  I-Ming Chen,et al.  A method for capturing the tacit knowledge in the surface finishing skill by demonstration for programming a robot , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[19]  Stefan Schaal,et al.  Robot Programming by Demonstration , 2009, Springer Handbook of Robotics.

[20]  Martin B.G. Jun,et al.  Evaluation of a spindle-based force sensor for monitoring and fault diagnosis of machining operations , 2002 .

[21]  Soichi Ibaraki,et al.  Monitoring Method of Cutting Force by Using Additional Spindle Sensors , 2006 .

[22]  Gerry Byrne,et al.  An Integrated Force Sensor Solution for Process Monitoring of Drilling Operations , 2007 .

[23]  John Kenneth Salisbury,et al.  Contact Sensing from Force Measurements , 1990, Int. J. Robotics Res..