Interactive Computer Play in the Pursuit of Gait Optimization for Children With Cerebral Palsy

Exercise therapy delivered through interactive computer play (ICP) has been shown to be effective for improving gross motor skills, and ultimately gait, in children with cerebral palsy (CP). This chapter provides an overview of CP, its impact on, gait and the current physical therapy (PT) standard of care. The history of the home exercise program (HEP) component of standard PT care is described, along with the potential for using ICP to improve HEP. ICP systems are surveyed, and their defining features discussed. The current therapeutic use of ICP is described and directions for further development to enhance therapeutic utility presented. A theoretical framework to support ICP implementation, self-determination theory (SDT), is outlined, and an example of its exploration in a pilot effort is provided. An example of healthcare system barriers to rapid uptake of ICP is presented along with alternative strategies for deployment and recommendations for further research.

Gait Optimization Method for Humanoid Robots Based on Parallel Comprehensive Learning Particle Swarm Optimizer Algorithm

To improve the fast and stable walking ability of a humanoid robot, this paper proposes a gait optimization method based on a parallel comprehensive learning particle swarm optimizer (PCLPSO). Firstly, the key parameters affecting the walking gait of the humanoid robot are selected based on the natural zero-moment point trajectory planning method. Secondly, by changing the slave group structure of the PCLPSO algorithm, the gait training task is decomposed, and a parallel distributed multi-robot gait training environment based on RoboCup3D is built to automatically optimize the speed and stability of bipedal robot walking. Finally, a layered learning approach is used to optimize the turning ability of the humanoid robot. The experimental results show that the PCLPSO algorithm achieves a quickly optimal solution, and the humanoid robot optimized possesses a fast and steady gait and flexible steering ability.

Scaffolded Learning of Bipedal Walkers: Bootstrapping Ontogenetic Development

Bipedal locomotion has several key challenges, such as balancing, foot placement, and gait optimization. We reach optimality from a very early age by using natural supports, such as our parent’s hands, chairs, and training wheels, and bootstrap a new knowledge from the recently acquired one. In this paper, we propose a scaffolded learning method from an evolutionary robotics perspective, where a biped creature achieves stable and independent bipedal walking while exploiting the natural scaffold of its changing morphology to create a third limb. Hence, we compare three conditions of scaffolded learning to reach bipedalism, and we prove that a performance-based scaffold is the most conducive to accelerate the learning of ontogenetic bipedal walking. Beyond a pedagogical experiment, this work presents a powerful tool to accelerate learning on robots.