Presented the functional body model at the IROS 2012 in Portugal. The article shows in simulation how the dynamic model can be recruited to solve the inverse task in motor control and coordinate the movement of all the joints of the six legged walker.
In this paper we introduce an internal body model for the control of a hexapod walker. The internal model deals with a highly complex robotic structure of 22 degrees of freedom and coordinates the single joint movements to achieve an overall stable and adaptive walking behavior. It is implemented as a hierarchical recurrent neural network consisting of different levels of abstraction which are tightly intertwined. We demonstrate the feasibility of the concept by applying the model to a simulated robot and show how the different levels of the body model interact and how this allows to scale the model even further. While the internal model is used in this context explicitly for motor control, it is also a predictive model and can be applied for sensor fusion.
Citation: Schilling, M., Paskarbeit, J., Schmitz, J., Schneider, A., and Cruse, H. (2012), “Grounding an Internal Body Model of a Hexapod Walker – Control of Curve Walking in a Biological Inspired Robot—Control of Curve Walking in a Biological Inspired Robot”. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012, pages 2762-2768.