Trajectory Generation for a Lower Limb Exoskeleton for Sit-to-Stand Transition Using a Genetic Algorithm

Abstract

Population of the world above the age of 65 years is increasing rapidly. Aging causes weakening of human joints which increases constraints on mobility of the body. Sit-to-Stand (STS), an important part of Activities of Daily Living (ADL) is one of the motions that is affected because of weakened joints. With the lack of personal care there is going to be a need for devices which can assist the aging population in STS. We propose the use of a lower-limb exoskeleton as an assistive device. One of the main challenges in this area is to generate a human like reference trajectory for exoskeleton to follow. This paper proposes the use of Genetic Algorithm (GA), to generate reference trajectories for the joint angles for lower limb exoskeleton for STS transition. The fitness function for the GA presented here is constructed based on the fact that for a successful STS center of mass (COM) needs to stay in the area of support. After the trajectory generation a simple controller is proposed to control a 3 degrees of freedom exoskeleton. The dynamics of the system being controlled are modelled as an inverse 3 degrees of freedom pendulum and the equations are derived using the Euler-Lagrange equation. The highly non-linear dynamics are linearized using an input-output feedback linearization technique. A PD controller is presented for this linearized dynamic system and the validation of the controller is done using simulations. Simulation results show that GA successfully generates a human like trajectory which eliminates the need to use motion tracking system for measuring human trajectories.

“Elbows Out”—Predictive Tracking of Partially Occluded Pose for Robot-Assisted Dressing

“…The technologies associated with robotics implemented for assisted living are being investigated for the range of ADL including walking [13] and guidance [8], nursing [20], sitto-stand [23] [3], bathing [21], and feeding [2] [28]. There are several groups pursuing research interests specifically in the area of dressing, some of whom deal especially with occlusions.…”

Feedback Control Design for Robust Comfortable Sit-to-Stand Motions of 3D Lower-Limb Exoskeletons

“…• Literature: To the best of our knowledge, there currently isn't a way of systematically choosing control objectives for highly constrained systems. When we use the control objectives in [10], [14], [16]- [19], [22], [28], [49] and a QP-enhanced input-output linearizing controller from [10], [19], we find that a 0.02 m increase in chair height results in foot contact violations of over 100 N.…”

“…We next discuss a dynamic chair-to-stand motion similar to the quasi-static motion used in the literature, where the CoM is first shifted over the feet and then the joints are extended [10], [14]. In this case, the standing domain is divided into two separate domains governed by the same equations of motions, standing shift and standing extend.…”

“…Hand-crafted trajectories are applicable when only a few joint trajectories are needed, such as with simplified models; of course, they may not take full advantage of the exoskeleton's capabilities. The use of dynamic movement primitives [15] or optimization methods such as the minimum jerk criterion [17], [30], constrained optimization [32], [33], or genetic algorithms [14], [34], have been employed to address the disadvantages of other methods. For instance, a constrained optimization problem can ensure that a designed sit-to-stand motion explicitly accounts for torque bounds.…”

“…To robustly perform the sit-to-stand motion, it is important that the chosen controller can track a desired trajectory in the presence of disturbances. There are several controllers that have been used in literature such as the computed-torque or input-output feedback linearization controller [10], [14], [22], [24], sliding mode controller [18], fuzzy controller [47], proportional-integral-derivative based controller [19], [27], [29], [48], impedance controller [15], and LQR [10], [31].…”