Compliance Shaping for Control of Strength Amplification Exoskeletons with Elastic Cuffs

Abstract

Exoskeletons which amplify the strength of their operators can enable heavy-duty manipulation of unknown objects. However, this type of behavior is difficult to accomplish; it requires the exoskeleton to sense and amplify the operator's interaction forces while remaining stable. But, the goals of amplification and robust stability when connected to the operator fundamentally conflict. As a solution, we introduce a design with a spring in series with the force sensitive cuff. This allows us to design an exoskeleton compliance behavior which is nominally passive, even with high amplification ratios. In practice, time delay and discrete time filters prevent our strategy from actually achieving passivity, but the designed compliance still makes the exoskeleton more robust to spring-like human behaviors. Our exoskeleton is actuated by a series elastic actuator (SEA), which introduces another spring into the system. We show that shaping the cuff compliance for the exoskeleton can be made into approximately the same problem as shaping the spring compliance of an SEA. We therefore introduce a feedback controller and gain tuning method which takes advantage of an existing compliance shaping technique for SEAs. We call our strategy the "double compliance shaping" method. With large amplification ratios, this controller tends to amplify nonlinear transmission friction effects, so we additionally propose a "transmission disturbance observer" to mitigate this drawback. Our methods are validated on a single-degree-of-freedom elbow exoskeleton.Proposition 1 (Systems in Parallel). The parallel inter-

Formulating and Deploying Strength Amplification Controllers for Lower-Body Walking Exoskeletons

“…And the essence of this design space is a bandwidth limitation on the control. This bandwidth limit, and its impact on coupled human–exoskeleton stability, has been studied in the context of single degree of freedom exoskeleton systems He et al (2019a) ; Thomas et al (2019) ; Huang et al (2020) ; He et al (2020) , and we will use the single degree of freedom case as a heuristic for understanding the tuning of the amplification task’s K ( s ) filter elements in our multi-DOF exoskeleton. While this heuristic omits several obvious nonlinear effects and inter-task couplings in the full system, it captures the basic problem of human–exoskeleton instability that can occur when bandwidth limits are ignored.…”

“…We conducted a set of simple tests to demonstrate the difference between gravity compensation and human strength amplification. These tests aimed to demonstrate an improvement in amplification stability relative to previous controllers developed for the exoskeleton and its previous partial prototypes (the 1-DOF testbed from He et al (2019a) ; Thomas et al (2019) , a two degree of freedom leg, and a previous revision on the same lower-body design) under the same project Campbell (2018) , which was a condition of our using the exoskeleton. 8…”

“…Designing a machine to be passive Colgate and Hogan (1988) ; Hogan (1989) ; Colgate and Brown (1994) ; Adams and Hannaford (1999) can also be seen as a robust control problem: such designs guarantee stability against a very wide range of “human” behaviors—the set of all passive transfer functions. Our prior work Thomas et al (2019) ; He et al (2019a) ; He et al (2019b) ; He et al (2020) has studied this stability problem for a table-mounted elbow exoskeleton.…”

“…4 ); 3) an amplification task that accomplishes strength amplification in Cartesian space ( Sec. 2 ); and 4) a heuristic tuning strategy for the amplification filter, which is based on He et al (2019a) and Thomas et al (2019) ( Sec. 3 ).…”

Robust Estimator-Based Safety Verification: A Vector Norm Approach

“…Uncertain robot model parameters and the lack of direct human state knowledge bring extra difficulty to the stabilization of human-robot systems. Methods such as robust loop shaping [1], [2], [3], model reference adaptive control [4] and energy shaping control [5] aim to balance the closed loop stability and performance of physical human robot interaction systems. However, there is no backup controller if these systems fail to maintain safety, because backup safety controllers require full state availability.…”