Kinematic Interactions Between Orthotic Robot and a Human

Szykiedans, K.

doi:10.1007/978-3-319-15847-1_26

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…The trajectory‐based controller requires proper pHRI models to sustain the bidirectional power flow between humans and robots. The ideal pHRI model enables exoskeleton robots to instantly adapt to the wearer's voluntary and involuntary movements; to this end, proper pHRI controller development should consider anthropometric design, body fixations, joints alignment, and actuation control (Farris et al., 2013; Szykiedans, 2015; S. Wang et al., 2015). For example, research headed by Chotiprayanakul developed a human–robot–environment interaction interface that allows collision‐free motion planning in a grit‐blasting activity during the construction of steel bridges (Chotiprayanakul et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

Gait trajectory‐based interactive controller for lower limb exoskeletons for construction workers

Ren¹,

Luo²,

et al. 2021

Computer aided Civil Eng

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Lower limb exoskeletons (LLEs) are sets of mechanical devices used to support the action of human lower limbs. This recently developed technology has unprecedented potential in the construction industry by increasing the strength, endurance, and other physical capabilities of construction workers. For safety considerations, LLEs need reliable and responsive controllers to closely match their mechanical operation with human gait in a synchronous manner. This research proposes the use of physical human–robot interactive (pHRI) controllers that are suitable for construction tasks. The proposed pHRI integrates a gait trajectory‐based musculoskeletal model with iterative control algorithms. To minimize the trajectory tracking error between LLEs and human lower limbs, the gait dynamic was modeled as a spring damping and impedance model for supporting and swing phases. An iterative adaptive controller was developed for trajectory tracking and predication. To validate the proposed model, an in‐lab experiment to simulate typical construction activities was conducted, allowing us to assess tracking error. The experiment results suggest that the proposed model can minimize the trajectory tracking error to a level acceptable for safe operation. The iterative controllers allow fast error convergence for different construction scenarios with proper calibration. Therefore, the proposed pHRI iterative controllers are reliable and suitable for complicated activities within the dynamic working conditions intrinsic to construction sites.

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