Abstract
This paper investigates the extension of an admittance control scheme toward learning and adaptation of its setpoints to achieve controllable bucket fill factor for robotic excavation of fragmented rock. A previously developed Dig Admittance Controller (DAC) is deployed on a 14-tonne capacity robotic load-haul-dump (LHD) machine, and full-scale excavation experiments are conducted with a rock pile at an underground mine to determine how varying DAC setpoints affect bucket fill factor. Results show that increasing the throttle setpoint increases the bucket fill factor and increasing the bucket’s reference velocity setpoint decreases the bucket fill factor. Further, the bucket fill factor is consistent for different setpoint values. Based on these findings, a learning framework is postulated to learn DAC setpoint values for a desired bucket fill factor over successive excavation iterations. Practical implementation problems such as bucket stall and wheel-slip are also addressed, and improvements to the DAC design are suggested to mitigate these problems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Buchli, J., Stulip, F., Theodorou, E., Schaal, S.: Learning variable impedance control. Int. J. Robot. Res. 30(7), 820–833 (2011)
Dadhich, S., Bodin, U., Andersson, U.: Key challenges in automation of earth-moving machines. Autom. Constr. 68, 212–222 (2016)
Dadhich, S., Bodin, U., Sandin, F., Andersson, U.: Machine learning approach to automatic bucket fill. In: Proceedings of 24th Mediterranean Conference on Control and Automation, Athens, Greece, pp 1260–1265 (2016)
Dimeas, F., Aspragathos, N.: Reinforcement learning of variable admittance control for human-robot co-manipulation. In: Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany, pp. 1011–1016 (2015)
Dobson, A.A., Marshall, J.A., Larsson, J.: Admittance control for robotic loading: Underground field trials with an LHD. In: Proceedings of the 10th Conference on Field and Service Robotics (FSR), Toronto, Ontario, Canada (2015)
Dobson, A.A., Marshall, J.A., Larsson, J.: Admittance control for robotic loading: Design and experiments with a 1-tonne loader and a 14-tonne LHD. Field Serv. Robot. J. Field Robot. 34(1), 123–150 (2017)
Haddadin, S., Croft, E.: Springer Handbook of Robotics, 2nd edn. Chap 69–Physical Human-Robot Interaction, pp. 1835–1874. Springer International Publishing, Switzerland (2016)
Hemami, A., Hassani, F.: An overview of autonomous loading of bulk material. In: Proceedings of the 26th International Symposium on Automation Robotics in Construction (ISARC), Austin, Texas, pp. 405–411 (2009)
Kim, Y.J., Seo, J., Kim, H., Kim, K.G.: Impedance and admittance control for respiratory motion compensation during robotic needle insertion—a preliminary test. Int. J. Med. Robot. Comput. Assisted Surg. 1–10 (2016)
Kronander, K., Billard, A.: Stability considerations for variable impedance control. IEEE Trans. Robot. 32(5), 1298–1305 (2016)
Li, Y., Ge, S.: Impedance learning for robots interacting with unknown envirnonments. IEEE Trans. Control Syst. Technol. 22(4), 1422–1432 (2014)
Maeda, G.J., Manchester, I.R., Rye, D.C.: Combined ILC and disturbance observer for the rejection of near-repetitive disturbances, with application to excavation. IEEE Trans. Control Syst. Technol. 23(5), 1754–1769 (2015)
Marshall, J.A., Murphy, P.F., Daneshmend, L.K.: Toward autonomous excavation of fragmented rock: full-scale experiments. IEEE Trans. Autom. Sci. Eng. 5(3), 562–566 (2008)
Villani, L., De Schutter, L.: Springer Handbook of Robotics, 2nd edn. Chap 9–Force Control, pp. 195–220. Springer, Switzerland (2016)
Wang, C., Li, Y., Ge, S.S., Lee, T.H.: Reference adaptation for robots in physical interactions with unknown environments. IEEE Trans. Cybern. https://doi.org/10.1109/TCYB.2016.2562698 (2016)
Yamawaki, T., Ishikawa, H., Yashima, M.: Iterative learning of variable impedance control for human-robot cooperation. In: Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, pp. 839–844 (2016)
Acknowledgements
This work was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) under project RGPIN-2015-04025, the Swedish Knowledge Foundation (KK-stiftelsen) under project 20150282, and by Atlas Copco Rock Drills AB (Sweden). This work was completed while the second author was a Visiting Professor at the Centre for Applied Autonomous Sensor Systems (AASS) in the School of Science and Technology at Örebro University, Sweden.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Fernando, H.A., Marshall, J.A., Almqvist, H., Larsson, J. (2018). Towards Controlling Bucket Fill Factor in Robotic Excavation by Learning Admittance Control Setpoints. In: Hutter, M., Siegwart, R. (eds) Field and Service Robotics. Springer Proceedings in Advanced Robotics, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-67361-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-67361-5_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67360-8
Online ISBN: 978-3-319-67361-5
eBook Packages: EngineeringEngineering (R0)