Motion Planning of Upper-Limb Exoskeleton Robots: A Review

Abstract

(1) Background: Motion planning is an important part of exoskeleton control that improves the wearer’s safety and comfort. However, its usage introduces the problem of trajectory planning. The objective of trajectory planning is to generate the reference input for the motion-control system. This review explores the methods of trajectory planning for exoskeleton control. In order to reduce the number of surveyed papers, this review focuses on the upper limbs, which require refined three-dimensional motion planning. (2) Methods: A systematic search covering the last 20 years was conducted in Ei Compendex, Inspect-IET, Web of Science, PubMed, ProQuest, and Science-Direct. The search strategy was to use and combine terms “trajectory planning”, “upper limb”, and ”exoskeleton” as high-level keywords. “Trajectory planning” and “motion planning” were also combined with the following keywords: “rehabilitation”, “humanlike motion“, “upper extremity“, “inverse kinematic“, and “learning machine “. (3) Results: A total of 67 relevant papers were discovered. Results were then classified into two main categories of methods to plan trajectory: (i) Approaches based on Cartesian motion planning, and inverse kinematics using polynomial-interpolation or optimization-based methods such as minimum-jerk, minimum-torque-change, and inertia-like models; and (ii) approaches based on “learning by demonstration” using machine-learning techniques such as supervised learning based on neural networks, and learning methods based on hidden Markov models, Gaussian mixture models, and dynamic motion primitives. (4) Conclusions: Various methods have been proposed to plan the trajectories for upper-limb exoskeleton robots, but most of them plan the trajectory offline. The review approach is general and could be extended to lower limbs. Trajectory planning has the advantage of extending the applicability of therapy robots to home usage (assistive exoskeletons); it also makes it possible to mitigate the shortages of medical caregivers and therapists, and therapy costs. In this paper, we also discuss challenges associated with trajectory planning: kinematic redundancy and incompatibility, and the trajectory-optimization problem. Commonly, methods based on the computation of swivel angles and other methods rely on the relationship (e.g., coordinated or synergistic) between the degrees of freedom used to resolve kinematic redundancy for exoskeletons. Moreover, two general solutions, namely, the self-tracing configuration of the joint axis and the alignment-free configuration of the joint axis, which add the appropriate number of extra degrees of freedom to the mechanism, were employed to improve the kinematic incompatibility between human and exoskeleton. Future work will focus on online trajectory planning and optimal control. This will be done because very few online methods were found in the scope of this study.

Kinematic of the Position and Orientation Synchronization of the Posture of a n DoF Upper-Limb Exoskeleton with a Virtual Object in an Immersive Virtual Reality Environment

“…The recent technological advances that emerged in the last decade, including digital manufacturing and rapid prototyping, have boosted the development of these devices. Exoskeleton design requires careful attention to provide natural motion of the users without endangering their safety [4,5], which can be achieved by the application of biomimetic design methods [6].…”

Wearable upper limb robotics for pervasive health: a review

“…Gopura et al [13] and Muhammad et al [14] comprehensively reviewed upper limb exoskeleton system designs and Rasedul et al [15] compared the research prototypes and commercial types of upper limbs. Some articles specifically performed literature reviews for key components for wearable upper limb robotics including mechanical designs [16], control strategies [17], actuation systems [18], and motion planning [19]. Most of these articles are for rigid exoskeletons.…”

Model for predicting the angles of upper limb joints in combination with sEMG and posture capture

“…Training strategies to relieve upper limb fatigue are developed and adjusted based on fatigue characteristics. As both the theory and technology of rehabilitation robots advance quickly, exoskeleton robots of upper limbs have become a major source of support for rehabilitation training, and they are widely used in therapies provided for patients with motion dysfunction [3]. Exoskeleton rehabilitation robots are primarily used to improve a patient's exercise capacity by expanding the range of motion of the upper limb joints.…”