Many places in the world are too rugged or enclosed for vehicles to access. Even today, material transport to such areas is limited to manual labor and beasts of burden. Modern advancements in wearable robotics may make those methods obsolete. Lower extremity exoskeletons seek to supplement the intelligence and sensory systems of a human with the significant strength and endurance of a pair of wearable robotic legs that support a payload. This article first outlines the use of Clinical Gait Analysis data as the framework for the design of such a system at UC Berkeley. This data is used to design the exoskeleton degrees of freedom and size its actuators. It will then give an overview of one of the control schemes implemented on the BLEEX. The control algorithm described here increases the system closed loop sensitivity to its wearer’s forces and torques without any measurement fromthe wearer (such as force, position, or electromyogram signal). The control algorithm uses the inverse dynamics of the exoskeleton, scaled by a number smaller than unity, as a positive feedback controller. This controller almost destabilizes the system since it leads to an overall loop gain slightly smaller than unity and results in a large sensitivity to all wearer’s forces and torques thereby allowing the exoskeleton to shadow its wearer.

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