Dynamic Model of a Humanoid Exoskeleton of a Lower Limb with Hydraulic Actuators

Głowiński, Sebastian; Obst, Maciej; Majdanik, Sławomir; Potocka-Banaś, Barbara

doi:10.3390/s21103432

Cited by 27 publications

(16 citation statements)

References 34 publications

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“…For example, it could help prevent risks in robot assisted surgery [32], where excessive grip force may cause tissue damage. In future, if we have the opportunity to acquire more data, especially from the novice, the further study of the training effect and the force pattern development could be conducted, which is hopefully to deliver insight to junior surgeons training [33], exoskeletons devel-oping [34], rehabilitation robot design [35] and tactile internet implementation [36][37][38]. Moreover, we are building a new glove system with more advanced grip sensors [39], which are smaller and more flexible.…”

Section: Discussionmentioning

confidence: 99%

Making Sense of Complex Sensor Data Streams

Liu¹,

Dresp-Langley

2021

Electronics

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This concept paper draws from our previous research on individual grip force data collected from biosensors placed on specific anatomical locations in the dominant and non-dominant hand of operators performing a robot-assisted precision grip task for minimally invasive endoscopic surgery. The specificity of the robotic system on the one hand, and that of the 2D image-guided task performed in a real-world 3D space on the other, constrain the individual hand and finger movements during task performance in a unique way. Our previous work showed task-specific characteristics of operator expertise in terms of specific grip force profiles, which we were able to detect in thousands of highly variable individual data. This concept paper is focused on two complementary data analysis strategies that allow achieving such a goal. In contrast with other sensor data analysis strategies aimed at minimizing variance in the data, it is necessary to decipher the meaning of intra- and inter-individual variance in the sensor data on the basis of appropriate statistical analyses, as shown in the first part of this paper. Then, it is explained how the computation of individual spatio-temporal grip force profiles allows detecting expertise-specific differences between individual users. It is concluded that both analytic strategies are complementary and enable drawing meaning from thousands of biosensor data reflecting human performance measures while fully taking into account their considerable inter- and intra-individual variability.

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Section: Discussionmentioning

confidence: 99%

Making Sense of Complex Sensor Data Streams

Liu¹,

Dresp-Langley

2021

Electronics

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“…This further challenge rehabilitation of the impaired limb due to the addition of extra weight to the already afflicted limb and discomfort to the user. Furthermore, devices designed in past, such as those actuated using pneumatic artificial muscles (PAMS) [2,3], actuated using hydraulic actuators [4], actuated using motors [5][6][7] actuates combination of ankle-kneehip (AKH) joint only in the sagittal plane. The lower limb motion has only been modelled in the sagittal plane, and frontal plane motion (hip adduction) has either been ignored or allowed passively in such designs.…”

Section: Introductionmentioning

confidence: 99%

Feasibility Study of Cable Routing for Bi-Planar Trajectory Tracking in Cable Driven Lower Limb Exoskeleton

Prasad¹,

El‐Rich²,

Awad³

et al. 2022

Preprint

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Although Cable driven rehabilitation devices (CDRD) have advantages over traditional link-driven devices, including lightweight, ease of reconfiguration, remote actuation, etc, the majority of existing lower-limb CDRD is limited to rehabilitation in the sagittal plane. In this work, we extend our previous sagittal plane model (2DOF) to accommodate hip motion in the frontal plane (abduction/adduction) toward studying the feasibility of tracking bi-planar motion (combined frontal and sagittal plane motion) via intra-planar cable routing. Two optimization problems have been formulated to estimate an optimal location of the hip cuffs, first to estimate the optimal cuff location at each time step to identify a single ‘averaged’ optimal cuff location and second to calculate a single optimal cuff location for the entire gait cycle. The optimization solutions identified for the 3DOF model revealed that optimization of the location of cuffs on the anterior and posterior side of the hip joint for 4 cable configuration is not sufficient to generate the desired bi-planar motion. For simultaneous tracking of the bi-planar motion, 2 additional cables have been added at hip joints and are routed in an intra-planar manner. The simulation result with the 3DOF model confirmed successful bi-planar trajectory tracking. The various number of cables and cable routings for tracking bi-planar motion will be studied in future work.

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“…For the lower limb exoskeleton, the human walking trajectory is random and does not need to be planned, so the inverse dynamics problem has more practical significance. Establishing an accurate dynamic model can not only accurately solve the forces and moments of each joint under the motion state, but also is a prerequisite for selecting the driving system of the exoskeleton robot and ensuring the control accuracy [8].…”

Section: Introductionmentioning

confidence: 99%

Comparison of dynamic models for the lower limb exoskeleton based on absolute and relative coordinates

Xu¹

2022

International Conference on Mechanisms and Robotics (ICMAR 2022)

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A precise and accurate dynamic model of the lower limb exoskeleton is particularly important for the optimization of the exoskeleton mechanical structure parameters and the design of the control system. Different scholars choose different ways of modeling, which can be generally based on absolute coordinates and relative coordinates. In order to analyze the correctness of the two modeling methods, the dynamic model of the lower limb exoskeleton with 2 degrees of freedom in absolute coordinates and relative coordinates is established by using Lagrange equation. The contribution of this paper is that by comparing the torque expressions of hip and knee joint under the two modeling methods and combining with the derivation process, the correctness of the dynamic model under the two coordinate systems is qualitatively analyzed. This provides a reference for researchers to accurately model the lower limb exoskeleton.

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Dynamic Model of a Humanoid Exoskeleton of a Lower Limb with Hydraulic Actuators

Cited by 27 publications

References 34 publications

Making Sense of Complex Sensor Data Streams

Making Sense of Complex Sensor Data Streams

Feasibility Study of Cable Routing for Bi-Planar Trajectory Tracking in Cable Driven Lower Limb Exoskeleton

Comparison of dynamic models for the lower limb exoskeleton based on absolute and relative coordinates

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