1 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland RP 15 Force estimation based on proprioceptive sensors for teleoperation in radioactive environments Project: 6 th June st June 2014 Enrique del Sol / Oxford Technologies Ltd. Supervisor: Robin Scott

2 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Background Information ESR: Enrique del Sol Acero Supervisor: Robin Scott Host institution: Oxford Technologies Ltd. University: Universidad Politécnica de Madrid PhD Supervisor: Manuel Ferre

3 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Contents 1.Aim and Overview 2.Force estimation 3.Closed Loop Simulation 4.Conclusion and additional remarks

4 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Industrial Robot. No backdrivable in general. Haptic master kinematically dissimilar to the slave Commanding position Receiving force feedback based on proprioceptive sensors Radioactive area. No electronics allowed. No force sensors due radiation and cost. Teleoperation of an industrial robot DEXTER 20 © Oxford Technologies Ltd 1. Aim and Overview

5 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Introduction: Position-Position teleoperation

6 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland 6 dof Force \ Torque sensor Introduction: Force-Position teleoperation Robot model

7 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland PP VS FP teleoperation Position – Position 1.Requires positional error to produce the force feedback. 2.Drag effect is produced on the master when moves in free space since appears a positional error with respect the slave. 3.It does not require any force sensor 4.It is very stable and it is very well known 5.It cannot work with non- backdrivable slaves.

8 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland 1.Aim and Overview 2.Force estimation 3.Closed Loop Simulation 4.Conclusion and additional remarks

9 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland The starting point is the robotics dynamics equation: The external forces can be estimated by applying the kinematic information contained in the robot Jacobian, obtaining (2): (1) (2) Force estimation: Robotics dynamics equation

Force estimation: Robotics dynamics equation II Brushless AC motors For hydraulic actuators based on servo valves: A joint is moved at a constant speed and the average torque is measured. For characterization purposes the friction had to be expressed in a more linear way. Dynamic terms: Force estimation based on proprioceptive sensors for teleoperation in radioactive environments A great number of manipulators present a closed loop j1 j33 2 j2 j4 j j6j5 j3 3b 3c chord nodes arcs Defining a spanning tree of the main graph Any algorithm like Newton-Euler can be applied to the spanning tree.

11 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Force estimation: Parameters identification  Preliminary identification experiments are needed.  Robot in motion  Only the robot dynamic coefficients can be identified (not all the links parameters)  In order to use the model, one needs to know the values of the robot dynamic properties such as: link masses, inertias, centre of gravity of each link, etc.  Robot manufacturers provide at most only a few principal dynamic parameters ( e.g., link masses)  Estimates can be found with CAD tools (e.g. assuming uniform density) but they might not provide enough accuracy for some circumstances. A priori knowledge Kinematic and geometric information Modelling Trajectory parameterization Robot excitation Position differentiation Parameter identification by LMS Parameter optimization Robot identification procedure Validation Validate model Satisfactory model? Not satisfactory Model specification

12 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland 3 Different approaches tested Force estimation: 3 approaches Direct evaluation of robotics dynamics equation Conventional State observers Conventional + Sliding observers

13 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Force estimation: Experimental setup PC Running LabView 2011 NI-PXI, running slave control NI-PXI running master control and force estimation algorithm Kraft GRIPS Hydraulic manipulator

14 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Force estimation: Direct evaluation of robotics dynamics equation Issues found: Errors due position differentiation to obtain speed and acceleration. Conventional velocity calculation VS Savitzky-Golay filter order 2 with 10 elements Conventional velocity calculation VS Savitzky-Golay filter order 2 with 51 elements Estimation problems due model unnacuracies

15 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Force estimation: Conventional observers Dynamic model of the robot with external forces : Robot space state equations: Robot space state observer: Robot observer error: Differentiating the observer error and grouping terms 0 0 The external torque turns out being proportional to the positional error. Error dynamics

16 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland The force estimation with Luenberger (traditional) observers presents steady state errors due the model errors. Results with conventional observers

17 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Force estimation: Sliding observers Dynamic model of the robot with external forces: Robot space state equations: Robot space state sliding observer: Robot observer error: Differentiating the observer error and grouping terms 0 0 The external torque turns out being the sum of K2 times the positional error and K4 times the sign of the error 0

18 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Force estimation: Force estimation with sliding observers Luenberger + Sliding observer Luenberger observer The force estimation adding sliding gains improves greatly, moreover during the steady state where the estimation error is now very small even in presence of modelling errors. 12% error

19 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Video: Force estimation with sliding observers

20 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland 1.Aim and Overview 2.Force estimation 3.Closed Loop Simulation 4.Conclusion and additional remarks

21 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland PP VS model based FP teleoperation The performance of the PP algorithm depends on the control. The performance of FP depends on the observer gains. In steady state zeros error is reached with Sliding observers.

22 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland 1.Aim and Overview 2.Force estimation 3.Closed Loop Simulation 4.Conclusion and additional remarks

23 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland A new method of robust force estimation based on sliding observers has been developed to be used on teleoperation. A dissimilar kinematic problem has been solved in order to teleoperate dissimilar master-slave. This method does not require a priori any filtering and thus, it produces zero delay. Forces at tip can be estimated with a minimum accuracy of 12%. It has been tested under a simulator for comparing control methods developed in Simulink. It also has been tested under real circumstances. A dynamic model of a parallelogram robot has been created. It has been developed a methodology for identifying the parameters of such parallelogram robot. Conclusions and remarks

24 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Conclusions and remarks PURESAFE RP interactions: Interaction with RP 8 on robot modelling, Interaction with RP 11 on assistive teleoperation with augmented reality Interaction with UPM researchers Goals accomplished? Succesful results with oportunities of extending the research in OTL. Impact: 2 conferences, 1 journal already published, 1 journal expected Future research lines: Applying this method closing the loop on a real scenario

25 Final Conference, 19th – 23rd January 2015 Geneva, Switzerland Questions?