Robots in machining

Abstract Robotic machining centers offer diverse advantages: large operation reach with large reorientation capability, and a low cost, to name a few. Many challenges have slowed down the adoption or sometimes inhibited the use of robots for machining tasks. This paper deals with the current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control. Recent research addressing deburring, milling, incremental forming, polishing or thin wall machining is presented. We discuss various processes in which robots need to deal with significant process forces while fulfilling their machining task.

[1]  Pascal Ray,et al.  Dynamic characterization of machining robot and stability analysis , 2016 .

[2]  Ming-June Tsai,et al.  Robotic polishing of precision molds with uniform material removal control , 2009 .

[3]  Wolfgang Hintze,et al.  Offline simulation of path deviation due to joint compliance and hysteresis for robot machining , 2017 .

[4]  Eric Courteille,et al.  Off-line compensation of the tool path deviations on robotic machining: Application to incremental sheet forming , 2013 .

[5]  Kim Doang Nguyen,et al.  On Algorithms for Planning S-Curve Motion Profiles , 2008 .

[6]  Ilian A. Bonev,et al.  An experimental study on the vibration response of a robotic machining system , 2013 .

[7]  Berend Denkena,et al.  Adaptronic Systems in Robot Manufacturing , 2011 .

[8]  Jean-Jacques E. Slotine,et al.  Robot analysis and control , 1988, Autom..

[9]  Jae-Bok Song,et al.  Precision robotic deburring based on force control for arbitrarily shaped workpiece using CAD model matching , 2013 .

[10]  Imin Kao,et al.  Conservative Congruence Transformation for Joint and Cartesian Stiffness Matrices of Robotic Hands and Fingers , 2000, Int. J. Robotics Res..

[11]  Eiichi Yoshida,et al.  M-TRAN: self-reconfigurable modular robotic system , 2002 .

[12]  Jun Zhang,et al.  Design of a self-reconfigurable wireless network system for modular self-reconfigurable robots , 2012, 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[13]  Gregory S. Chirikjian,et al.  Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.

[14]  Peter I. Corke,et al.  Robotics, Vision and Control - Fundamental Algorithms in MATLAB® , 2011, Springer Tracts in Advanced Robotics.

[15]  Jyhwen Wang,et al.  An efficient force prediction strategy for single point incremental sheet forming , 2017 .

[16]  Hans Christian Schmidt,et al.  Enhanced Absolute Accuracy of an Industrial Milling Robot Using Stereo Camera System , 2016 .

[17]  Gary M. Bone,et al.  An Automated Planning, Control, and Inspection System for Robotic Deburring , 1992 .

[18]  Dragan Milutinovic,et al.  A method for off-line compensation of cutting force-induced errors in robotic machining by tool path modification , 2014 .

[19]  Yoshio Kawauchi,et al.  Structure decision method for self organising robots based on cell structures-CEBOT , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[20]  Xuan F. Zha,et al.  Optimal pose trajectory planning for robot manipulators , 2002 .

[21]  Wenlei Xiao,et al.  Redundancy and optimization of a 6R robot for five-axis milling applications: singularity, joint limits and collision , 2012, Prod. Eng..

[22]  Xiao-Wei Tu,et al.  Calibration of Modular Reconfigurable Robots Based on a Hybrid Search Method , 2010 .

[23]  Geir Hovland,et al.  Off-line path correction of robotic face milling using static tool force and robot stiffness , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[24]  Miguel Ángel Sebastián,et al.  Overview of the State of Robotic Machining: Current Situation and Future Potential , 2015 .

[25]  Sang-Min Park,et al.  An automatic tool changer and integrated software for a robotic die polishing station , 2006 .

[26]  Xuefeng Zhou,et al.  Task-oriented inverse kinematics of modular reconfigurable robots , 2013, 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[27]  Berend Denkena,et al.  Enabling an Industrial Robot for Metal Cutting Operations , 2015 .

[28]  Berend Denkena,et al.  Simulation Based Planning of Machining Processes with Industrial Robots , 2016 .

[29]  Paolo Fino,et al.  The Capacity Of Cold Spray Additive Manufacturing Technology For Metallic Part Repairing , 2018 .

[30]  Zengxi Pan,et al.  Machining with flexible manipulator: toward improving robotic machining performance , 2005, Proceedings, 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics..

[31]  Eberhard Abele,et al.  Modeling and Identification of an Industrial Robot for Machining Applications , 2007 .

[32]  Ali Karim,et al.  POSE AND FEED-DIRECTION DEPENDENCY ANALYSIS FOR MILLING TASKS WITH INDUSTRIAL ROBOTS , 2018 .

[33]  Rasit Köker,et al.  A genetic algorithm approach to a neural-network-based inverse kinematics solution of robotic manipulators based on error minimization , 2013, Inf. Sci..

[34]  Anders Robertsson,et al.  Robot Joint Modeling and Parameter Identification Using the Clamping Method , 2013, MIM.

[35]  Mark Yim,et al.  Brake design for dynamic modular robots , 2010, 2010 IEEE International Conference on Robotics and Automation.

[36]  S. A. Tobias.  Machine-tool vibration , 1965 .

[37]  Henrik Hautop Lund,et al.  Modular ATRON: modules for a self-reconfigurable robot , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[38]  Qiang Zhan,et al.  Hand–eye calibration and positioning for a robot drilling system , 2012 .

[39]  Mats Björkman,et al.  Cost-efficient drilling using industrial robots with high-bandwidth force feedback , 2010, Robotics and Computer-Integrated Manufacturing.

[40]  Xavier Balandraud,et al.  FEM-Based Generation of Stiffness Maps , 2015, IEEE Transactions on Robotics.

[41]  Carlos Martínez,et al.  Human-robot collaboration in manufacturing: Quantitative evaluation of predictable, convergent joint action , 2013, IEEE ISR 2013.

[42]  Tarek M. Sobh,et al.  Modeling A Deburring Process, Using DELMIA V5® , 2008, EIAT/IETA.

[43]  Jun Wu,et al.  Review: An overview of dynamic parameter identification of robots , 2010 .

[44]  Cesare Rossi,et al.  Robot trajectory planning by assigning positions and tangential velocities , 2013 .

[45]  Marcello Pellicciari,et al.  An Offline Programming Method for the Robotic Deburring of Aerospace Components , 2013 .

[46]  A. Valente,et al.  Development of multi-level adaptive control and scheduling solutions for shop-floor automation in reconfigurable manufacturing systems , 2011 .

[47]  Chao-Yin Hsiao,et al.  A method of tool path compensation for repeated machining process , 1998 .

[48]  Changhoon Kim,et al.  Modeling and Control of a New Robotic Deburring System , 2007 .

[49]  Horst Meier,et al.  Increasing the part accuracy in dieless robot-based incremental sheet metal forming , 2009 .

[50]  Ping Zhang,et al.  Online robot calibration based on vision measurement , 2013 .

[51]  Phil Webb,et al.  Robotic edge profiling of complex components , 2011, Ind. Robot.

[52]  A. Gasparetto,et al.  A new method for smooth trajectory planning of robot manipulators , 2007 .

[53]  Lutfi Taner Tunc,et al.  Experimental study on investigation of dynamics of hexapod robot for mobile machining , 2015 .

[54]  Alan N Bramley,et al.  Incremental sheet forming process for small batch and prototype parts , 2001 .

[55]  Dazhong Wu,et al.  Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation , 2015, Comput. Aided Des..

[56]  Yin Guo,et al.  Real-time thermal error compensation method for robotic visual inspection system , 2014 .

[57]  Ratna Babu Chinnam,et al.  Product design and manufacturing process based ontology for manufacturing knowledge reuse , 2019, J. Intell. Manuf..

[58]  Michael Hofbaur,et al.  Modular re-configurable robot drives , 2010, 2010 IEEE Conference on Robotics, Automation and Mechatronics.

[59]  Bertold Bongardt,et al.  Sheth-Uicker Convention Revisited , 2013 .

[60]  Eberhard Abele,et al.  Wechselwirkungen von Fräsprozess und Maschinenstruktur am Beispiel des Industrieroboters , 2008 .

[61]  Paul Sas,et al.  INTELLIGENT JOINT FAULT DIAGNOSIS OF INDUSTRIAL ROBOTS , 1998 .

[62]  T. Huang,et al.  Conceptual design and dimensional synthesis for a 3-DOF module of the TriVariant-a novel 5-DOF reconfigurable hybrid robot , 2005, IEEE Transactions on Robotics.

[63]  P. Elosegui,et al.  Measurement of the dynamic model of a PUMA 560 robot using experimental modal analysis , 1994 .

[64]  Masafumi Sakamoto,et al.  Development of Metal-Mold Polishing Robot System with Contact Pressure Control Using CAD/CAM Data , 1990 .

[65]  Gunnar Bolmsjö,et al.  Extending an industrial robot controller: implementation and applications of a fast open sensor interface , 2005, IEEE Robotics & Automation Magazine.

[66]  Erdem Ozturk,et al.  Robotic assisted milling for increased productivity , 2018 .

[67]  S. R. Munasinghe,et al.  Reduced jerk joint space trajectory planning method using 5-3-5 spline for robot manipulators , 2014, 7th International Conference on Information and Automation for Sustainability.

[68]  Maxime Gautier,et al.  DIDIM: A new method for the dynamic identification of robots from only torque data , 2008, 2008 IEEE International Conference on Robotics and Automation.

[69]  Manuel Beschi,et al.  A human mimicking control strategy for robotic deburring of hard materials , 2018, Int. J. Comput. Integr. Manuf..

[70]  Shreyes N. Melkote,et al.  CCT-based mode coupling chatter avoidance in robotic milling , 2017 .

[71]  John M. Hollerbach,et al.  Redundancy resolution of manipulators through torque optimization , 1987, IEEE J. Robotics Autom..

[72]  Hui Zhang,et al.  Chatter analysis of robotic machining process , 2006 .

[73]  Maxime Gautier,et al.  Dynamic identification of the Kuka LWR robot using motor torques and joint torque sensors data , 2014 .

[74]  Shreyes N. Melkote,et al.  Effect of Robot Dynamics on the Machining Forces in Robotic Milling , 2017 .

[75]  Hans Christian Schmidt,et al.  Machining of large scaled CFRP-Parts with mobile CNC-based robotic system in aerospace industry , 2017 .

[76]  Berend Denkena,et al.  Holistic process planning chain for robot machining , 2017, Prod. Eng..

[77]  Eberhard Abele,et al.  Spanende Bearbeitung mit Industrierobotern - Thermische Einflüsse auf die Bearbeitungsgenauigkeit , 2013 .

[78]  E. Croft,et al.  Smooth and time-optimal trajectory planning for industrial manipulators along specified paths , 2000 .

[79]  Sébastien Briot,et al.  Compliance error compensation in robotic-based milling , 2014, ArXiv.

[80]  Libor Preucil,et al.  Global motion planning for modular robots with local motion primitives , 2013, 2013 IEEE International Conference on Robotics and Automation.

[81]  Farhad Aghili,et al.  A Reconfigurable Robot With Lockable Cylindrical Joints , 2009, IEEE Transactions on Robotics.

[82]  Pascal Ray,et al.  Dynamic modeling and stability prediction in robotic machining , 2017 .

[83]  Juan J. Marquez,et al.  Process modeling for robotic polishing , 2005 .

[84]  Lutfi Taner Tunc,et al.  Effects of Chattering on Surface Integrity in Robotic Milling of Alloy 690 , 2017 .

[85]  Horst Meier,et al.  Comparison and validation of implementations of a flexible joint multibody dynamics system model for an industrial robot , 2011 .

[86]  Gunther Reinhart,et al.  Qualification of Standard Industrial Robots to Cope with Sophisticated Assembly Tasks , 1998 .

[87]  Mark Yim,et al.  New locomotion gaits , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[88]  Saravana Perumaal,et al.  Synchronized trigonometric S-Curve trajectory for jerk-Bounded Time-Optimal pick and Place Operation , 2012, Int. J. Robotics Autom..

[89]  Mark Yim,et al.  PolyBot: a modular reconfigurable robot , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[90]  Ming J. Tsai,et al.  Robotic Path Planning for an Automatic Mold Polishing System , 2004, Int. J. Robotics Autom..

[91]  Anatoly Pashkevich,et al.  Accuracy Improvement of Robot-Based Milling Using an Enhanced Manipulator Model , 2014, ArXiv.

[92]  Alessandro Gasparetto,et al.  Experimental validation and comparative analysis of optimal time-jerk algorithms for trajectory planning , 2012 .

[93]  Ali Karim,et al.  Experimental determination of compliance values for a machining robot , 2018, 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[94]  Anna Valente,et al.  Reconfigurable industrial robots , 2016 .

[95]  Lei Yuan,et al.  A Study of Chatter in Robotic Machining and A Semi- Active Chatter Suppression Method Using Magnetorheological Elastomers (MREs) , 2017 .

[96]  Julian M. Allwood,et al.  A structured search for applications of the incremental sheet-forming process by product segmentation , 2005 .

[97]  J. D. Barnfather,et al.  Development and testing of an error compensation algorithm for photogrammetry assisted robotic machining , 2016 .

[98]  Christian Boehlmann,et al.  Referencing Strategies for High Accuracy Machining of Large Aircraft Components with Mobile Robotic Systems , 2017 .

[99]  Alexander Verl,et al.  Detection of Workpiece Shape Deviations for Tool Path Adaptation in Robotic Deburring Systems , 2016 .

[100]  Fengjie Tian,et al.  Modeling and control of robotic automatic polishing for curved surfaces , 2016 .

[101]  Anna Valente,et al.  Trajectory Planning for Reconfigurable Industrial Robots Designed to Operate in a High Precision Manufacturing Industry , 2016 .

[102]  Alex Graves,et al.  Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.

[103]  Robert Bogue,et al.  Finishing robots: a review of technologies and applications , 2009, Ind. Robot.

[104]  Ulrich Schneider,et al.  Experimental Investigation of Sources of Error in Robot Machining , 2013 .

[105]  Diego Galar Pascual,et al.  Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and DIagnosis , 2015 .

[106]  Sergey Levine,et al.  Path integral guided policy search , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[107]  Ricardo Franco Mendoza Garcia,et al.  Mechanical design of odin, an extendable heterogeneous deformable modular robot , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[108]  Berend Denkena,et al.  Design and optimization of a machining robot , 2017 .

[109]  Ulrich Schneider,et al.  Programming System for Efficient Use of Industrial Robots for Deburring in SME Environments , 2012, ROBOTIK.

[110]  Tao Wei,et al.  Signal decomposition and fault diagnosis of a SCARA robot based only on tip acceleration measurement , 2009, 2009 International Conference on Mechatronics and Automation.

[111]  Maxime Gautier,et al.  A Generic Instrumental Variable Approach for Industrial Robot Identification , 2014, IEEE Transactions on Control Systems Technology.

[112]  Ulrich Schneider,et al.  Integrated approach to robotic machining with macro/micro-actuation , 2014 .

[113]  Bernd Kuhlenkötter,et al.  Geometry-dependent parameterization of local support in robot-based incremental sheet forming , 2018 .

[114]  Stéphane Caro,et al.  Joint stiffness identification of six-revolute industrial serial robots , 2011 .

[115]  Paul A. Meehan,et al.  Efficient force prediction for incremental sheet forming and experimental validation , 2014 .

[116]  A. Castano,et al.  The Conro modules for reconfigurable robots , 2002 .

[117]  Heinz Wörn,et al.  CoBoLD — A bonding mechanism for modular self-reconfigurable mobile robots , 2011, 2011 IEEE International Conference on Robotics and Biomimetics.

[118]  Lutfi Taner Tunc,et al.  Tool path pattern and feed direction selection in robotic milling for increased chatter-free material removal rate , 2017 .

[119]  Martin A. Riedmiller.  Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method , 2005, ECML.

[120]  Auke Jan Ijspeert,et al.  An experimental study on the role of compliant elements on the locomotion of the self-reconfigurable modular robots Roombots , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[121]  Hongguang Wang,et al.  Research on kinematics of modular reconfigurable robots , 2011, 2011 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems.

[122]  Stefan Schaal,et al.  2008 Special Issue: Reinforcement learning of motor skills with policy gradients , 2008 .

[123]  George Q. Huang,et al.  Multi-agent based real-time production scheduling method for radio frequency identification enabled ubiquitous shopfloor environment , 2014, Comput. Ind. Eng..

[124]  Yangsheng Xu,et al.  Motion Trajectory Planning of Space Manipulator for Joint Jerk Minimization , 2007, 2007 International Conference on Mechatronics and Automation.

[125]  Bijan Shirinzadeh,et al.  Enhanced stiffness modeling, identification and characterization for robot manipulators , 2005, IEEE Transactions on Robotics.

[126]  Julian Ricardo Diaz Posada,et al.  Position control of an industrial robot using an optical measurement system for machining purposes , 2013 .

[127]  H. Van Brussel,et al.  Condition Monitoring of Robot Joints Using Statistical and Nonlinear Dynamics Tools , 2003 .

[128]  Berend Denkena,et al.  Innovative Drive Concept for Machining Robots , 2013 .

[129]  Jie Liang,et al.  Robotic drilling system for titanium structures , 2011 .

[130]  Christian Baier.  Process and Software Chain for Combined Laser Cladding and Milling in Robot Systems , 2018 .

[131]  Julian Ricardo Diaz Posada,et al.  Automatic Programming and Control for Robotic Deburring , 2016 .

[132]  Alexander Verl,et al.  Challenges and obstacles in robot-machining , 2013, IEEE ISR 2013.

[133]  M. Spong,et al.  Robot Modeling and Control , 2005 .

[134]  Bin Wu,et al.  A shape adaptive motion control system with application to robotic polishing , 2005 .

[135]  Robert Bicker,et al.  The State of the Art in Research into the Condition Monitoring of Industrial Machinery , 2014 .

[136]  Frank Boochs,et al.  Increasing the accuracy of untaught robot positions by means of a multi-camera system , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

[137]  Shreyes N. Melkote,et al.  A Wireless Force-Sensing and Model-Based Approach for Enhancement of Machining Accuracy in Robotic Milling , 2016, IEEE/ASME Transactions on Mechatronics.

[138]  Milad Geravand,et al.  High accurate robotic drilling with external sensor and compliance model-based compensation , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[139]  L. Schuler.  Metal forming handbook , 1966 .

[140]  Aurelio Piazzi,et al.  Global minimum-jerk trajectory planning of robot manipulators , 2000, IEEE Trans. Ind. Electron..

[141]  Yoshimi Takeuchi,et al.  Automation of Polishing Work by an Industrial Robot : System of Polishing Robot , 1993 .

[142]  Luis Gracia,et al.  Calibration and control of a redundant robotic workcell for milling tasks , 2011, Int. J. Comput. Integr. Manuf..

[143]  Lutfi Taner Tunc,et al.  Investigation of the effects of Stewart platform-type industrial robot on stability of robotic milling , 2016 .

[144]  Takashi Miyoshi,et al.  Automation of Polishing Process for a Cavity Surface on Dies and Molds by Using an Expert System , 1993 .

[145]  Matthias Kurze,et al.  Modellbasierte Regelung von Robotern mit elastischen Gelenken ohne abtriebsseitige Sensorik , 2008 .

[146]  L. F. F. Furtado,et al.  A method to improve the use of 6-dof robots as machine tools , 2017 .

[147]  Kriangkrai Waiyagan,et al.  Modelling of Robotic Drilling , 2017 .

[148]  Fumin Zhang,et al.  An online real-time path compensation system for industrial robots based on laser tracker , 2016 .

[149]  H. Tam,et al.  Robotic polishing of free-form surfaces using scanning paths , 1999 .

[150]  Iuliu Vasilescu,et al.  Miche: Modular Shape Formation by Self-Disassembly , 2008, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[151]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[152]  Christian Moeller,et al.  High Accuracy Mobile Robotic System for Machining of Large Aircraft Components , 2016 .

[153]  Youcef Mezouar,et al.  Redundancy-based optimization approach to optimize robotic cell behaviour: application to robotic machining , 2015, Ind. Robot.

[154]  Fengfeng Xi,et al.  Module-Based Static Structural Design of a Modular Reconfigurable Robot , 2010 .

[155]  Matthias Weigold,et al.  Kompensation der Werkzeugabdrängung bei der spanenden Bearbeitung mit Industrierobotern , 2008 .

[156]  Horst Meier,et al.  CAx Process Chain for Two Robots Based Incremental Sheet Metal Forming , 2012 .

[157]  T. Selvaraj,et al.  Vision Assisted Robotic Deburring of Edge Burrs in Cast Parts , 2014 .

[158]  Benoît Furet,et al.  Joint stiffness identification of industrial serial robots , 2011, Robotica.

[159]  Julian Ricardo Diaz Posada,et al.  Automatic Motion Generation for Robotic Milling Optimizing Stiffness with Sample-Based Planning , 2017 .

[160]  Alexander Verl,et al.  Analysis of the dynamic behavior of a six-axis industrial robot within the entire workspace in respect of machining tasks , 2017, 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[161]  Christian Moeller,et al.  Real Time Pose Control of an Industrial Robotic System for Machining of Large Scale Components in Aerospace Industry Using Laser Tracker System , 2017 .

[162]  Hui Zhang,et al.  Robotic machining from programming to process control: a complete solution by force control , 2008, Ind. Robot.

[163]  Ismael Lopez-Juarez,et al.  Acquisition of welding skills in industrial robots , 2015, Ind. Robot.

[164]  Ulrich Schneider,et al.  Improving robotic machining accuracy through experimental error investigation and modular compensation , 2016 .

[165]  Jorge Santolaria,et al.  Laser tracker-based kinematic parameter calibration of industrial robots by improved CPA method and active retroreflector , 2013 .

[166]  Michael F. Zäh,et al.  Improvement of the machining accuracy of milling robots , 2014, Prod. Eng..

[167]  Yusuf Altintas,et al.  Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design , 2000 .

[168]  Nikolaos G. Tsagarakis,et al.  VSA-CubeBot: A modular variable stiffness platform for multiple degrees of freedom robots , 2011, 2011 IEEE International Conference on Robotics and Automation.

[169]  Jan Peters,et al.  A Survey on Policy Search for Robotics , 2013, Found. Trends Robotics.

[170]  Ferdinand Freudenstein,et al.  Kinematic Synthesis of Linkages , 1965 .

[171]  Anna Valente,et al.  Smooth joint motion planning for high precision reconfigurable robot manipulators , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).

[172]  Hadas Kress-Gazit,et al.  High-level control of modular robots , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[173]  Aude Billard,et al.  Roombots-mechanical design of self-reconfiguring modular robots for adaptive furniture , 2009, 2009 IEEE International Conference on Robotics and Automation.

[174]  Sung-Rak Kim,et al.  A practical approach for minimum-time trajectory planning for industrial robots , 2010, Ind. Robot.

[175]  B. Hazel,et al.  Robotic approach to improve turbine surface finish , 2010, 2010 1st International Conference on Applied Robotics for the Power Industry.

[176]  Christian Brecher,et al.  Model-based process planning for milling operations using industrial robots , 2018, 2018 3rd International Conference on Control and Robotics Engineering (ICCRE).

[177]  Harvey Lipkin,et al.  A Note on Denavit-Hartenberg Notation in Robotics , 2005 .

[178]  Ulrik Pagh Schultz,et al.  Generalized programming of modular robots through kinematic configurations , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[179]  Shreyes N. Melkote,et al.  A Method for Mode Coupling Chatter Detection and Suppression in Robotic Milling , 2018, Journal of Manufacturing Science and Engineering.

[180]  Wei-Min Shen,et al.  On the complexity of optimal reconfiguration planning for modular reconfigurable robots , 2010, 2010 IEEE International Conference on Robotics and Automation.

[181]  Sébastien Briot,et al.  Elasto-Dynamic Model of Robotic Milling Process Considering Interaction Between Tool and Workpiece , 2012 .

[182]  Emulating self-reconfigurable robots - design of the SMORES system , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[183]  Sergey Levine,et al.  End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..

[184]  Yoshio Mizugaki,et al.  Fractal path generation for a metal-mold polishing robot system and its evaluation by the operability , 1992 .

[185]  Pascal Ray,et al.  Control of a Multi Degrees Functional Redundancies Robotic Cell for Optimization of the Machining Stability , 2017 .

[186]  A. Bottero,et al.  Adaptive control techniques and feed forward compensation of periodic disturbances in industrial manipulators , 2014, 2014 IEEE/ASME 10th International Conference on Mechatronic and Embedded Systems and Applications (MESA).

[187]  Elizabeth A. Croft,et al.  Jerk-bounded manipulator trajectory planning: design for real-time applications , 2003, IEEE Trans. Robotics Autom..

[188]  Emanuele Carpanzano,et al.  Smooth trajectory generation for industrial robots performing high precision assembly processes , 2017 .

[189]  Yusuf Altintas,et al.  Chatter stability in robotic milling , 2019, Robotics and Computer-Integrated Manufacturing.