Robot assisted mobility for functional learning of children with special needs

Mobility is a causal factor in development. Children with mobility impairments may rely upon power mobility for independence and thus require advanced driving skills to function independently. Our previous studies show that while infants can learn to drive directly to a goal using conventional joysticks in several months of training, they are unable to acquire the advanced skills such as direction driving and obstacle avoidance. Without adequate driving training, children are unable to explore the environment safely, the consequences of which may in turn increase their risk for developmental delay. The goal of this research therefore is to train children seated on mobile robots to purposefully and safely drive indoors. The hypothesis is that these impaired infants will benefit from mobility in their early years and attain childhood milestones, similar to their healthy peers.;This work presents a series of devices and training algorithms for functional motor learning in children. First, a mobile robot based wheelchair was built with a force-feedback joystick to train toddlers to steer using an `assist-as-needed' paradigm. In this paradigm, if the child steers the joystick outside a force tunnel centered on the desired direction, the driver experiences a bias force on the hand. We show results with a group study on typically-developing toddlers that such a haptic guidance algorithm is superior to training with a conventional joystick. We also provide a case study on two special needs children, under three years old, who learn to make sharp turns during driving, when trained over a five-day period with the force-feedback joystick using this algorithm. Then, an algorithm based on artificial potential fields to avoid obstacles was developed to train toddlers to navigate amidst obstacles using the same `assist-as-needed' paradigm. Ten typically-developing toddlers and one with spina-bifida who cannot independently walk were trained to drive a robot within an obstacle course. Results suggest that in this task, a force-feedback joystick also yields faster learning compared to the use of a conventional joystick.;Although many studies have shown that training with the `assist-as-needed' method can improve driving performance of children and adults, the effectiveness of such haptic assistance as a motor training strategy is still an open question. The essential aspect of the training is to keep the subjects constantly challenged. This work presents the first study to evaluate training with a repelling force versus an assisting force for learning of a line following task in a wheelchair through a force-feedback joystick. A robotic training wheelchair was designed that can accurately localize itself in the training environment, and the assisting and repelling force fields were implemented on the force-feedback joystick. Both the assisting force and the repelling force groups improved their driving skills. The error reductions of both groups were not statistically different under the current setting. We believe that this pilot study could provide a promising foundation regarding the effects of robotic wheelchair training algorithm on motor learning in children.;The ultimate goal of the mobility training is to let children learn to be social, that is, to interact with peers. A smart wheelchair was developed that can localize itself, map the environment, then plan an obstacle-free path to a goal, and ensure safety. Combined with a tracking system, this social assembly is able to set a force field to train subjects to drive towards a caregiver, a peer, or a group of peers. System feasibility was tested by designing a ball chasing game. Results show that the system could be promising in promoting socialization in children.;Although independent mobility via power mobility devices prevents development delays, it does little to encourage children's development of gross motor skills. This work presents a novel mobility interface for infants to explore the environment when they are placed in a prone position. Infants can maneuver the robot through a drive interface that utilizes a camera to detect the motion of markers attached to their legs. We expect that infants will learn to drive the device by swinging their legs. Specifically, our work demonstrates feasibility of this drive interface using data from two infants.