Berkeley Lower Extremity Exoskeleton Research Articles

Model-based Control with Interaction Predicting for Human-coupled Lower Exoskeleton Systems

Sensitivity Amplification Control (SAC) algorithm was first proposed in the augmentation application of the Berkeley Lower Extremity Exoskeleton (BLEEX). Since the SAC algorithm can greatly reduce the complexity of exoskeleton system, it is widely used in human augmentation applications. Nevertheless, the performance of the SAC algorithm depends on the accuracy of dynamic model parameters. In this paper, we propose a novel Model-based control with Interaction Predicting (MIP) strategy to lower dependency on the accurate dynamic model of the exoskeleton. The MIP consists of an interaction predictor and a model-based controller. The interaction predictor can predict motion trajectories of the pilot and substitute for the pilot to drive the exoskeleton through an impedance model. In proposed strategy, the model-based controller not only amplify the forces initiated by the interaction predictor, but more importantly the forces imposed by the pilot to correct the errors between the predictive motion trajectory and the intended motion trajectory of the pilot. Illustrative simulations and experimental results are presented to demonstrate the efficiency of the proposed strategy. Additionally, the comparisons with traditional model-based control algorithm are also presented to demonstrate the efficiency and superiority of the proposed control strategy for lowering dependency on dynamic models.

Biomechanical design of the Berkeley lower extremity exoskeleton (BLEEX)

Wheeled vehicles are often incapable of transporting heavy materials over rough terrain or up staircases. Lower extremity exoskeletons supplement human intelligence with the strength and endurance of a pair of wearable robotic legs that support a payload. This paper summarizes the design and analysis of the Berkeley lower extremity exoskeleton (BLEEX). The anthropomorphically based BLEEX has 7 DOF per leg, four of which are powered by linear hydraulic actuators. The selection of the DOF, critical hardware design aspects, and initial performance measurements of BLEEX are discussed.

Berkeley Human Exoskeleton Technology

In October 2003, the first functional load-bearing and energetically autonomous exoskeleton, called the Berkeley Lower Extremity Exoskeleton (BLEEX) was demonstrated, walking at the average speed of two miles per hour while carrying 75 pounds of load. The project, funded in 2000, tackled four fundamental technologies: the exoskeleton architectural design, a control algorithm, a body LAN to host the control algorithm, and an on-board power unit to power the actuators, sensors and the computers. The primary objective of this project at U.C. Berkeley is to develop the fundamental technologies associated with design and control of energetically autonomous Lower Extremity Exoskeletons that augment human strength and endurance during locomotion. BLEEX is comprised of two powered anthropomorphic legs, a power unit, and a backpack-like frame on which a variety of heavy loads can be mounted. This system provides its pilot (i.e., its wearer) the ability to carry significant loads on his/her back with minimal effort over any type of terrain. BLEEX allows the pilot to comfortably squat, bend, swing from side to side, twist, and walk on ascending and descending slopes, while also offering the ability to step over and under obstructions while carrying equipment and supplies. Because the pilot can carry significant loads for extended periods of time without reducing his/her agility, physical effectiveness increases significantly with the aid of this class of lower extremity exoskeletons.

Design of an electrically actuated lower extremity exoskeleton

Human exoskeletons add the strength and endurance of robotics to a human's innate intellect and adaptability to help people transport heavy loads over rough, unpredictable terrain. The Berkeley lower extremity exoskeleton (BLEEX) is the first human exoskeleton that was successfully demonstrated to walk energetically autonomous while supporting its own weight plus an external payload. This paper details the design of the electric motor actuation for BLEEX and compares it to the previously designed hydraulic actuation scheme. Clinical gait analysis data was used to approximate the torques, angles and powers required at the exoskeleton's leg joints. Appropriately sized motors and gearing are selected, and put through a thorough power analysis. The compact electric joint design is described and the final electric joint performance is compared with BLEEX's previous hydraulic actuation. Overall, the electric actuation scheme is about twice as efficient and twice as heavy as the hydraulic actuation.

Control and system identification for the Berkeley lower extremity exoskeleton (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.

Development of hybrid hydraulic–electric power units for field and service robots

Energetic autonomy of a hydraulic-based mobile robot requires a power source capable of both hydraulic and electrical power generation. The hydraulic power is used for locomotion, and the electric power is used for the control computer, sensors and other peripherals. In addition, the power source must be lightweight and quiet. This study presents several designs of internal combustion engine-based power units. Each power unit is evaluated with a Ragone plot which shows its performance over a wide range of operation times. Several hydraulic–electric power units (HEPUs) were built and successfully demonstrated on the Berkeley lower extremity exoskeleton (BLEEX). The best-performing design of the HEPUs, based upon the Ragone plot analysis, is described in detail. This HEPU produces constant pressure hydraulic power and constant voltage electric power. The pressure and voltage are controlled on board the power unit by a computer. A novel characteristic of this power unit is its cooling system in which hydraulic fluid is used to cool the engine cylinders. The prototype power unit weighs 27 kg and produces 2.3 kW (3.0 hp) hydraulic power at 6.9 MPa (1000 p.s.i.) and 220 W of electric power at 15 V DC.

The Berkeley Lower Extremity Exoskeleton

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.