KoroiBot: Improving humanoid walking capabilities by human-inspired mathematical models, optimization and learning
KoroiBot a three years project funded by the European Commission under FP7-ICT-2013-10. The goal of the project is to investigate the way humans walk, e.g., on stairs and slopes, on soft and slippery ground, over beams and seesaws and create mathematical models and learning methods for humanoid walking. The project will study human walking, develop techniques for increased humanoid walking performance and evaluate them on existing state of the art humanoid robots.
KIT leads the tasks concerning human walking experiments, the establishment of large scale human walking database and the development of human and humanoid models as basis for the development of general motion and control laws transfer rules between different embodiments and for the generation of different walking types. The developed models and transfer rules, we will study how to implement balancing and push recovery strategies to deal with different types of perturbation in free and constrained situations. Furthermore, we will investigate the role of prediction in walking as well as the role different sensory feedback such as vision, vestibular and foot haptics in balancing. Therefore, we will implement a control and action selection schema emphasizing predictive control mechanisms, which rely on the estimation of expected perturbation based on multimodal sensory feedback and past sensorimotor experience. The control schema will be validated in the context of prediction and selection of push recovery actions.