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The Berkeley Lower Extremity Exoskeleton is the first functional energetically autonomous load carrying human exoskeleton and was demonstrated at U.C. Berkeley, walking at the average speed of 0.9 m/s (2 mph) while carrying a 34 kg (75 lb) payload. The original published controller, called the BLEEX Sensitivity Amplification Controller, was based on positive feedback and was designed to increase the closed loop system sensitivity to its wearer's forces and torques without any direct measurement from the wearer. This controller was successful at allowing natural and unobstructed load support for the pilot. This article presents an improved control scheme we call "hybrid" BLEEX control that adds robustness to changing BLEEX backpack payload. The walking gait cycle is divided into stance control and swing control phases. Position control is used for the BLEEX stance leg (including the torso and backpack) and a sensitivity amplification controller is used for the swing leg. The controller is also designed to smoothly transition between these two schemes as the pilot walks. With hybrid control, the controller does not require a good model of the BLEEX torso and payload, which is difficult to obtain and subject to change as payload is added and removed. As a tradeoff, the position control used in this method requires the human to wear seven inclinometers to measure human limb and torso angles. These additional sensors require careful design to securely fasten them to the human and increase the time to don and doff BLEEX.

The Berkeley lower extremity exoskeleton (BLEEX) is an autonomous robotic device whose function is to increase the strength and endurance of a human pilot. In order to achieve an exoskeleton controller which reacts compliantly to external forces, an accurate model of the dynamics of the system is required. In this report, a series of system identification experiments was designed and carried out for BLEEX. As well as determining the mass and inertia properties of the segments of the legs, various non-ideal elements, such as friction, stiffness and damping forces, are identified. The resulting dynamic model is found to be significantly more accurate than the original model predicted from the designs of the robot.

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The first functional load-carrying and energetically autonomous exoskeleton was demonstrated at the University of California, Berkeley, walking at the average speed of 1.3m∕s(2.9mph) while carrying a 34kg(75lb) payload. Four fundamental technologies associated with the Berkeley lower extremity exoskeleton were tackled during the course of this project. These four core technologies include the design of the exoskeleton architecture, control schemes, a body local area network to host the control algorithm, and a series of on-board power units to power the actuators, sensors, and the computers. This paper gives an overview of one of the control schemes. The analysis here is an extension of the classical definition of the sensitivity function of a system: the ability of a system to reject disturbances or the measure of system robustness. The control algorithm developed here increases the closed-loop system sensitivity to its wearer’s forces and torques without any measurement from the wearer (such as force, position, or electromyogram signal). The control method has little robustness to parameter variations and therefore requires a relatively good dynamic model of the system. The trade-offs between having sensors to measure human variables and the lack of robustness to parameter variation are described.