Abstract
Curve walking is an important skill for multi-legged robot locomotion as it increases a robots’ maneuverability. We investigate whether a decentralized system can explain even complex walking behaviors like curve walking. Based on an analysis of the curve walking capabilities of the decentralized control architecture Walknet, we propose a couple of simple but effective modifications with a main focus on the coordination between leg controllers: controlling the step length, shifting the AEP (transition point from swing to stance), and decreasing the step length for the legs on the inside of the curve. In simulation, the modified architecture demonstrated a significant improvement in the stability of the curve walking performance for tight curves and even allows a smooth transition to extremely tight curves and turning on the spot. Furthermore, the system is tested on a real robot and showed good qualitative results and robust curve walking behavior.
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Notes
- 1.
Videos can be found in the publicly accessible git: https://gitlab.ub.uni-bielefeld.de/jsimmering/walknet-curve-walking-supporting-videos.git.
References
Buschmann, T., Ewald, A., von Twickel, A., Büschges, A.: Controlling legs for locomotion–insights from robotics and neurobiology. Bioinspiration Biomimetics 10(4), 041001 (2015). https://doi.org/10.1088/1748-3190/10/4/041001
Cruse, H.: What mechanisms coordinate leg movement in walking arthropods? Trends Neurosci. 13(1), 15–21 (1990)
Cruse, H., et al.: Walking: a complex behavior controlled by simple networks. Adapt. Behav. 3(4), 385–418 (1995). https://doi.org/10.1177/105971239500300403
Cruse, H., Kindermann, T., Schumm, M., Dean, J., Schmitz, J.: Walknet—a biologically inspired network to control six-legged walking. Neural Netw. 11(7), 1435–1447 (1998). https://doi.org/10.1016/S0893-6080(98)00067-7
Dürr, V., Ebeling, W.: The behavioural transition from straight to curve walking: Kinetics of leg movement parameters and the initiation of turning. J. Exp. Biol. 208(12), 2237–2252 (2005). https://doi.org/10.1242/jeb.01637
Dürr, V., Schmitz, J., Cruse, H.: Behaviour-based modelling of hexapod locomotion: linking biology and technical application. Arthropod Struct. Dev. 33(3), 237–250 (2004). https://doi.org/10.1016/j.asd.2004.05.004
Ijspeert, A.J.: Central pattern generators for locomotion control in animals and robots: a review. Neural Netw. 21(4), 642–653 (2008)
Jander, J.P.: Untersuchungen zum Mechanismus und zur zentralnervösen Steuerung des Kurvenlaufs bei Stabheuschrecken (Carausius morosus). Ph.D. thesis, Universität Köln (1982)
Kindermann, T.: Behavior and adaptability of a six-legged walking system with highly distributed control. Adapt. Behav. 9(1), 16–41 (2001)
Neftci, E.O., Averbeck, B.B.: Reinforcement learning in artificial and biological systems. Nature Mach. Intell. 1(3), 133–143 (2019)
Paskarbeit, J.: Consider the robot-abstraction of bioinspired leg coordination and its application to a hexapod robot under consideration of technical constraints. Ph.D. thesis, Universität Bielefeld (2017)
Rosano, H., Webb, B.: A dynamic model of thoracic differentiation for the control of turning in the stick insect. Biol. Cybern. 97(3), 229–246 (2007). https://doi.org/10.1007/s00422-007-0170-4
Schilling, M., Cruse, H.: ReaCog, a minimal cognitive controller based on recruitment of reactive systems. Front. Neurorobotics 11, 3 (2017)
Schilling, M., Hoinville, T., Schmitz, J., Cruse, H.: Walknet, a bio-inspired controller for hexapod walking. Biol. Cybern. 107(4), 397–419 (2013)
Schilling, M., Konen, K., Ohl, F.W., Korthals, T.: Decentralized deep reinforcement learning for a distributed and adaptive locomotion controller of a hexapod robot. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5335–5342. IEEE
Schilling, M., Melnik, A.: An approach to hierarchical deep reinforcement learning for a decentralized walking control architecture. In: Samsonovich, A.V. (ed.) BICA 2018. AISC, vol. 848, pp. 272–282. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-99316-4_36
Schilling, M., Melnik, A., Ohl, F.W., Ritter, H.J., Hammer, B.: Decentralized control and local information for robust and adaptive decentralized deep reinforcement learning. Neural Netw. 144, 699–725 (2021)
Schilling, M., et al.: A hexapod walker using a heterarchical architecture for action selection. Front. Comput. Neurosci. 7, 126 (2013)
Schilling, M., Paskarbeit, J., Ritter, H., Schneider, A., Cruse, H.: From adaptive locomotion to predictive action selection-Cognitive control for a six-legged walker. IEEE Trans. Rob. 38(2), 666–682 (2022)
Schilling, M., Paskarbeit, J., Schmitz, J., Schneider, A., Cruse, H.: Grounding an internal body model of a hexapod walker - control of curve walking in a biological inspired robot. In: Proceeding of International Conference on Intelligence Robots and Systems (2012)
Simmering, J.: Adapting the decentralized walknet architecture for improved curve walking in a six-legged phantomx. Master’s thesis, Bielefeld University (2021)
Acknowledgement
This research was supported by the research training group “Dataninja” (Trustworthy AI for Seamless Problem Solving: Next Generation Intelligence Joins Robust Data Analysis) funded by the German federal state of North Rhine-Westphalia.
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Simmering, J., Hermes, L., Schneider, A., Schilling, M. (2023). Adaptation of a Decentralized Controller to Curve Walking in a Hexapod Robot. In: Cascalho, J.M., Tokhi, M.O., Silva, M.F., Mendes, A., Goher, K., Funk, M. (eds) Robotics in Natural Settings. CLAWAR 2022. Lecture Notes in Networks and Systems, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-031-15226-9_26
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