UC Berkeley

There are 6.8 million people in the United States that have mobility disorders and must rely on the use of assistive devices to aid in locomotion \cite{kaye2000mobility}. The human body was designed for a particular bipedal locomotion pattern, and deviations from that method of locomotion can result in secondary injuries. Many of the current solutions for mobility disorders are primitive, such as crutches or canes if possible and wheelchairs when not. In recent years, more intelligent, robotic systems have been developed to aid this population that needs assistance walking. Among these new robotic solutions are robotic exoskeletons.

Robotic exoskeletons have become a more popular rehabilitation tool in recent years, particularly for those with spinal cord injury. There are currently three robotic exoskeletons with US Food and Drug Administration approval for clinical use. One barrier to wider adoption is the cost of these devices. To reduce cost, a more minimal design was developed at the Human Engineering and Robotics Laboratory at the University of California with only two actuators at the hips and a semi-passive locking mechanism at the knee. While this design can help reduce the weight and cost, it introduces additional complexity to the gait development due to the lack of actuation.

The gait development strategies discussed in this paper are inspired by clinical gait data collected from healthy subjects. After all, the ultimate goal of an exoskeleton system as a rehabilitation device is to rehabilitate the pilot to the point that the patient's gait is restored to a natural walking pattern and the device is no longer necessary. Using clinical gait data and biomechanical studies, several models are developed for the design considered. A kinematic model was developed to better understand the angular constraints during both single stance and double stance. A dynamic model was also developed that models the behaviour of the system for different phases of the gait. Finally all these models were linked together in a finite state machine to form a hybrid automaton. The finite state machine specifies the switching conditions for each state.

One method for gait development is to design gaits that are tunable such that the gait practitioner can tune the gait to the pilot's comfort and rehabilitation needs. In this endeavour, a kinematic model is used to define the constraints of the double stance phase. The gaits are then generated using a quartic polynomial spline using the node parameters from the kinematic analysis. This method empowers the gait practitioner by using tuning parameters that they understand from gait rehabilitation literature.

Another method for gait development is to use optimal gaits based on a hybrid automaton model of the system. The automaton implements three states or phases of the gait cycle including their associated dynamic models. Using this model, the gaits can be optimized for the torques necessary for these gaits under minimal input assumptions from the pilot in each of the phases. This optimization allows for a more detailed understanding of the system dynamics and an optimal gait given constraints of both the system and the gait cycle. Furthermore, the optimization method can be utilized as a gait generator that is tailored to each individual pilot, effectively reducing the workload of the gait practitioner.