Inverse kinematic analysis and trajectory planning of a modular upper limb rehabilitation exoskeleton

Li, Ge; Fang, Qianqian; Xu, Tian; Zhao, Jie; Cai, Hao; Zhu, Yanhe

doi:10.3233/thc-199012

Cited by 18 publications

(18 citation statements)

References 18 publications

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“…When the rotation speed of motor 2 is faster than that of motor 1, then the exoskeleton can achieve the abduction and extension or adduction and flexion movement of the shoulder joint. For more structural design details, one can refer to our previous work [33,34].…”

Section: Cable-actuated Parallel Exoskeleton Designmentioning

confidence: 99%

“…In order to better observe the driving torque of each motor of the exoskeleton after mapping motor motion to joint motion, this section designs a controller shown in Figure 3 based on joint angle decoupling introduced in detail in our previous paper [34] and conversion algorithm with the computational torque method for parallely connected exoskeleton robots and performs trajectory tracking control simulation based on the planned motor trajectory.…”

Section: System Stability Analysismentioning

confidence: 99%

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A Simplified Inverse Dynamics Modelling Method for a Novel Rehabilitation Exoskeleton with Parallel Joints and Its Application to Trajectory Tracking

Fang

et al. 2019

Mathematical Problems in Engineering

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In this paper, a new modular upper limb rehabilitation exoskeleton, which is actuated by a parallel mechanical structure, is designed to help stroke patients. For analysing the relationship between motor torque and joint torque of the novel exoskeleton, a conversion algorithm mapping motor motion to joint motion is developed here. Then, to simplify the dynamics model of exoskeleton with parallel actuated joints, the serial equivalence configuration dynamics of the exoskeleton is established to be equivalent to the parallel joints dynamics. Afterwards, a torque controller used for our exoskeleton is designed based on the proposed conversion algorithm and the inverse dynamics of exoskeleton. It should be noted that the controller mentioned above combines both conversion algorithm and joint position decoupling. At last, for verifying the effectiveness of the proposed algorithms, a trajectory tracking simulation is given, and the simulated results show the proposed algorithms are valid.

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Section: Cable-actuated Parallel Exoskeleton Designmentioning

confidence: 99%

Section: System Stability Analysismentioning

confidence: 99%

A Simplified Inverse Dynamics Modelling Method for a Novel Rehabilitation Exoskeleton with Parallel Joints and Its Application to Trajectory Tracking

Fang

et al. 2019

Mathematical Problems in Engineering

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“…However, in this way knowing or predicting the direction of the endpoint is a prerequisite. Authors in Li et al (2019) used the reverse coordinate method to complete the inverse kinematics solutions and also proposed a new multicubic polynomial-interpolation method for planning joint trajectories.…”

Section: Introductionmentioning

confidence: 99%

Using proposed optimization algorithm for solving inverse kinematics of human upper limb applying in rehabilitation robotic

2021

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The requirement to solve the problem of Inverse Kinetics (IK) plays a very important role in the robotics field in general, and especially in the field of rehabilitation robots, in particular. If the solutions of this problem are not suitable, it can cause undesirable damage to the patient when exercising. Normally, the problem of Inverse Kinematics in the robotics field, as well as the natural field, especially for redundant driven systems, often requires the application of a lot of techniques. The redundancy in Degree of Freedom (DoF), the nonlinearity of the system leads to solve inverse kinematics problem more challenge. In this study, we proposed to apply the self-adaptive control parameters in Differential Evolution with search space improvement (Pro-ISADE) to solve the problem for the human upper limb, which is a very typical redundancy model in nature. First of all, the angles of the joints were measured by a proposed Exoskeleton type Human Motion Capture System (E-HMCS) when the wearer performs some Activities of Daily Living (ADL) and athletic activities. The values of these measured angles joints then were put into the forward kinematics model to find the end effector trajectories. After having these orbits, they were re-fed into the proposed Pro-ISADE algorithm mentioned above to process the IK problem and obtain the predicted joints angular values. The experimental results showed that the predicted joints’ values closely follow the measured joints’ values. That demonstrates the ability to apply the Pro-ISADE algorithm to solve the problem of Inverse Kinetics of the human upper limb as well as the upper limb rehabilitation robot arm.

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“…Accordingly, proper trajectory planning is essential to the use of exoskeleton robots in home settings. Much work was done on trajectory planning for exoskeleton robots [8][9][10][11][12][13][14][15]. In this context, this paper deals with trajectory-planning problems, i.e., the computation of desired motion profiles for the actuation system of automatic machines.…”

Section: Introductionmentioning

confidence: 99%

“…However, it is difficult to solve the inverse kinematics problem because there is an infinite number of solutions [17]. Attempts to resolve the inverse kinematics problem in robotics have used many approaches, including Jacobian [12], optimization, dimensionality-reduction, and learning-based methods [18]. In [19], a method based on optimization was proposed to implicitly resolve inverse kinematics.…”

Section: Introductionmentioning

confidence: 99%

Motion Planning of Upper-Limb Exoskeleton Robots: A Review

2020

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(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.

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Inverse kinematic analysis and trajectory planning of a modular upper limb rehabilitation exoskeleton

Cited by 18 publications

References 18 publications

A Simplified Inverse Dynamics Modelling Method for a Novel Rehabilitation Exoskeleton with Parallel Joints and Its Application to Trajectory Tracking

A Simplified Inverse Dynamics Modelling Method for a Novel Rehabilitation Exoskeleton with Parallel Joints and Its Application to Trajectory Tracking

Using proposed optimization algorithm for solving inverse kinematics of human upper limb applying in rehabilitation robotic

Motion Planning of Upper-Limb Exoskeleton Robots: A Review

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