  Ankle push-off largely contributes to limb energy generation in human
walking, leading to smoother and more efficient locomotion. Providing this net
positive work to an amputee requires an active prosthesis, but has the
potential to enable more natural assisted locomotion. To this end, this paper
uses multi-contact models of locomotion together with force-based nonlinear
optimization-based controllers to achieve human-like kinematic behavior,
including ankle push-off, on a powered transfemoral prosthesis for 2 subjects.
In particular, we leverage model-based control approaches for dynamic bipedal
robotic walking to develop a systematic method to realize human-like walking on
a powered prosthesis that does not require subject-specific tuning. We begin by
synthesizing an optimization problem that yields gaits that resemble human
joint trajectories at a kinematic level, and realize these gaits on a
prosthesis through a control Lyapunov function based nonlinear controller that
responds to real-time ground reaction forces and interaction forces with the
human. The proposed controller is implemented on a prosthesis for two subjects
without tuning between subjects, emulating subject-specific human kinematic
trends on the prosthesis joints. These experimental results demonstrate that
our force-based nonlinear control approach achieves better tracking of human
kinematic trajectories than traditional methods.
