Design of a Hip Exoskeleton With Actuation in Frontal and Sagittal Planes

Chiu, Vincent L.; Raitor, Michael; Collins, Steven H.

doi:10.1109/tmrb.2021.3088521

Cited by 29 publications

(12 citation statements)

References 40 publications

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“…For example, the legs of the MIT cheetah robot have a force-magnitude bandwidth of ~ 100 Hz—about 50× faster than what was found in our experiment—and nearly no steady-state error or steady-state variability 17 , 37 . Wearable devices such as foot prostheses and leg exoskeletons demonstrate millisecond-scale control, enabling for accurate and rapid control of force 19 , 38 . Yet the agility of humans continues to be greater than that of state-of-the-art legged robots suggesting that human agility is achieved not through a greater control of leg forces, but by a greater understanding of what forces to apply.…”

Section: Discussionmentioning

confidence: 99%

Characterizing the performance of human leg external force control

Kudzia

Robinovich

Donelan

2022

Sci Rep

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Our legs act as our primary contact with the surrounding environment, generating external forces that enable agile motion. To be agile, the nervous system has to control both the magnitude of the force that the feet apply to the ground and the point of application of this force. The purpose of this study was to characterize the performance of the healthy human neuromechanical system in controlling the force-magnitude and position of an externally applied force. To accomplish this, we built an apparatus that immobilized participants but allowed them to exert variable but controlled external forces with a single leg onto a ground embedded force plate. We provided real-time visual feedback of either the leg force-magnitude or force-position that participants were exerting against the force platform and instructed participants to best match their real-time signal to prescribed target step functions. We tested target step functions of a range of sizes and quantified the responsiveness and accuracy of the control. For the control of force-magnitude and for intermediate step sizes of 0.45 bodyweights, we found a bandwidth of 1.8 ± 0.5 Hz, a steady-state error of 2.6 ± 0.9%, and a steady-state variability of 2.7 ± 0.9%. We found similar control performance in terms of responsiveness and accuracy across step sizes and between force-magnitude and position control. Increases in responsiveness correlated with reductions in other measures of control performance, such as a greater magnitude of overshooting. We modelled the observed control performance and found that a second-order model was a good predictor of external leg force control. We discuss how benchmarking force control performance in young healthy humans aids in understanding differences in agility between humans, between humans and other animals, and between humans and engineered systems.

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Section: Discussionmentioning

confidence: 99%

Characterizing the performance of human leg external force control

Kudzia

Robinovich

Donelan

2022

Sci Rep

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“…However, both passive and semi-active bionic legs cannot provide the user with active torque to meet the requirements of the user’s moderate energy consumption. In the normal human body, the muscles of the legs will provide active torque to generate thrust and reduce the impact when landing ( Chiu et al, 2021 ). Therefore, passive bionic legs will cause more consumption to the user and are not suitable for road conditions such as slopes and stairs.…”

Section: Related Workmentioning

confidence: 99%

Detection and Analysis of Bionic Motion Pose of Single Leg and Hip Joint Based on Random Process

Zhang

Seung-Soo

2022

Front. Bioeng. Biotechnol.

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Based on the spectral representation method of random function and combined with memoryless nonlinear translation theory, this paper analyzes the transformation relationship between potential Gaussian random process and non-Gaussian random process, and successfully generates a stationary non-Gaussian random process that conforms to the target non-Gaussian random process. For the non-stationary non-Gaussian random process simulation, on the basis of the stationary Gaussian random process, the intensity non-stationary uniform modulation model is used to modulate it, and combined with the nonlinear translation theory, the non-stationary non-Gaussian random process conforming to the target non-Gaussian random process is obtained. Aiming at the single-leg bouncing model based on the flexible rotary hip joint, the stability of its bouncing motion under passive motion is studied, and the influence of the flexible hip rotary joint on the motion stability is analyzed by comparing the single-leg bouncing motion characteristics of the free rotary hip joint. Based on the inverse dynamic control of the air phase, the fixed point distribution of the single-leg bounce of the flexible rotary hip joint was improved, and the function of the flexible rotary hip joint in the energy conversion of the bouncing motion was studied by establishing the energy consumption evaluation function. The kinematic performance verification, dynamic performance verification, dynamic parameter identification verification, and modal experiment simulation analysis were carried out for the built experimental platform, and the comparison and analysis with its theoretical model were carried out. The results show that the theoretical motion trajectory of the test mobile platform is basically consistent with the actual motion trajectory in the X and Y directions, and there is a small error in the Z-axis direction, and the error is within an acceptable range, indicating that the experimental platform system can be used to simulate the human hip joint. There is a large error between the theoretical value of the driving torque calculated by the theoretical value of the dynamic parameters and the measured value, and the dynamic theoretical model cannot accurately predict the driving torque. The predicted value of the driving torque calculated by using the identification value of the dynamic parameters is in good agreement with the measured torque, and its confidence is increased by 10–16%, indicating that the dynamic parameter identification method in this paper has a high degree of confidence.

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“…Next, we show that our model's predictions are useful for downstream control tasks by providing collision avoidance assistance to a virtual human in a simulated environment. Our control experiment setup follows that of a hip exoskeleton emulator with actuation to adjust foot placement and centerof-mass states [7]. We approximate center-of-mass as the root joint and directly control its orientation.…”

Section: Collision Avoidance Assistance Using Copilotmentioning

confidence: 99%

“…To enable such detailed prediction, input videos are captured from cameras mounted to several human body joints, which provide a holistic multi-view context of the human motion and surroundings. Our hardware setup follows that of Chiu et al [7] with additional visual sensors for fullbody collision prediction.…”

Section: Introductionmentioning

confidence: 99%

COPILOT: Human Collision Prediction and Localization from Multi-view Egocentric Videos

Pan¹,

Shen²,

Rempe³

et al. 2022

Preprint

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To produce safe human motions, assistive wearable exoskeletons must be equipped with a perception system that enables anticipating potential collisions from egocentric observations. However, previous approaches to exoskeleton perception greatly simplify the problem to specific types of environments, limiting their scalability. In this paper, we propose the challenging and novel problem of predicting human-scene collisions for diverse environments from multi-view egocentric RGB videos captured from an exoskeleton. By classifying which body joints will collide with the environment and predicting a collision region heatmap that localizes potential collisions in the environment, we aim to develop an exoskeleton perception system that generalizes to complex real-world scenes and provides actionable outputs for downstream control. We propose COPILOT, a video transformer-based model that performs both collision prediction and localization simultaneously, leveraging multi-view video inputs via a proposed joint space-timeviewpoint attention operation. To train and evaluate the model, we build a synthetic data generation framework to simulate virtual humans moving in photo-realistic 3D environments. This framework is then used to establish a dataset consisting of 8.6M egocentric RGBD frames to enable future work on the problem. Extensive experiments suggest that our model achieves promising performance and generalizes to unseen scenes as well as real world. We apply COPILOT to a downstream collision avoidance task, and successfully reduce collision cases by 29% on unseen scenes using a simple closed-loop control algorithm.

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Design of a Hip Exoskeleton With Actuation in Frontal and Sagittal Planes

Cited by 29 publications

References 40 publications

Characterizing the performance of human leg external force control

Characterizing the performance of human leg external force control

Detection and Analysis of Bionic Motion Pose of Single Leg and Hip Joint Based on Random Process

COPILOT: Human Collision Prediction and Localization from Multi-view Egocentric Videos

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