Improving performance of robots using human-inspired approaches: a survey

Qiao, Hong; Zhong, Shanlin; Chen, Ziyu; Wang, Hongze

doi:10.1007/s11432-022-3606-1

Cited by 51 publications

(20 citation statements)

References 215 publications

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“…For example, the collision ground simulation experiment system built by Boeing Company of the United States ( Motaghedi and Stamm, 2005 ), and the collision ground simulation experiment system of McDonnell Douglas Aerospace Department of the United States ( Ananthakrishnan et al, 1996 ). Realizing high performance of ordinary robots is one of the core problems in robotic research ( Chen and Qiao, 2020a , Qiao et al, 2022b ). With the development of robot application and the combination of deep learning technology and robots ( Qi and Su, 2022 ), robots are increasingly intelligent ( Chen and Qiao, 2020b , Wang et al, 2022 ) and behaving more and more like human beings ( Su et al, 2022b ).…”

Section: Our Choicementioning

confidence: 99%

Actuation delay compensation of robots in semi-physical test

Zhang

He²,

Xu³

et al. 2023

Front. Neurorobot.

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In general, the traditional spacecraft semi-physical docking tests include the evaluation of docking and separation performance. However, these tests often rely on “specific” equipment, such as specially designed actuators and fast-response hydraulic systems, to meet the stringent dynamic response requirements of semi-physical testing. In this paper, a novel docking test platform is designed based on a general-purpose industrial manipulator using 3-D force and 3-D torque sensors. Different from the traditional solution, this novel platform is well-assembled and cost-effective. Furthermore, an actuation delay compensation method is introduced to improve the performance. Finally, the proposed method is evaluated using simulations. The results show that the novel method is with promising performance in terms of actuation delay compensation.

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Section: Our Choicementioning

confidence: 99%

Actuation delay compensation of robots in semi-physical test

Zhang

He²,

Xu³

et al. 2023

Front. Neurorobot.

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show abstract

“…In recent years, with the development of unmanned docking technology Qiao et al, 2022;Li et al, 2017;Xue et al, 2022;, people have put forward higher requirements for the accuracy and stability of unmanned docking, especially for autonomous docking of unmanned vehicles and other fields (Li et al, 2021;Zhao et al, 2023;Wang et al, 2021). How to quickly and accurately achieve unmanned autonomous docking of ground vehicles has become a research hot spot (Qiao et al, 2014;Li et al, 2018;Su et al, 2021;Qiao et al, 2001;Yang et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, with the development of unmanned docking technology (Chen et al , 2020; Chen and Qiao, 2020; Qiao et al , 2022; Yang et al , 2018; Li et al , 2017; Xue et al , 2022; Li et al , 2015), people have put forward higher requirements for the accuracy and stability of unmanned docking, especially for autonomous docking of unmanned vehicles and other fields (Li et al , 2021; Chen et al , 2021; Zhao et al , 2023; Wang et al , 2021). How to quickly and accurately achieve unmanned autonomous docking of ground vehicles has become a research hot spot (Qiao et al , 2014; Chen and Qiao, 2020; Li et al , 2018; Su et al , 2021; Qiao et al , 2001; Yang et al , 2014). Considering the characteristics of high motion accuracy and fast response speed of multi degree of freedom (DOF) platform (Chen et al , 2022; Li et al , 2020; Li et al , 2020; Chen et al , 2021; Li et al , 2019), the mechanism design based on multi DOF platform is the main research direction to realize autonomous docking of unmanned aerial vehicles.…”

Section: Introductionmentioning

confidence: 99%

Stewart-inspired parallel spatial docking robot: design, analysis and experimental results

Zhan

Zhang

Chen

et al. 2023

RIA

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Purpose This paper aims to focus on the spatial docking task of unmanned vehicles under ground conditions. The docking task of military unmanned vehicle application scenarios has strict requirements. Therefore, how to design a docking robot mechanism to achieve accurate docking between vehicles has become a challenge. Design/methodology/approach In this paper, first, the docking mechanism system is described, and the inverse kinematics model of the docking robot based on Stewart is established. Second, the genetic algorithm-based optimization method for multiobjective parameters of parallel mechanisms including workspace volume and mechanism flexibility is proposed to solve the problem of multiparameter optimization of parallel mechanism and realize the docking of unmanned vehicle space flexibility. The optimization results verify that the structural parameters meet the design requirements. Besides, the static and dynamic finite element analysis are carried out to verify the structural strength and dynamic performance of the docking robot according to the stiffness, strength, dead load and dynamic performance of the docking robot. Finally, taking the docking robot as the experimental platform, experiments are carried out under different working conditions, and the experimental results verify that the docking robot can achieve accurate docking tasks. Findings Experiments on the docking robot that the proposed design and optimization method has a good effect on structural strength and control accuracy. The experimental results verify that the docking robot mechanism can achieve accurate docking tasks, which is expected to provide technical guidance and reference for unmanned vehicles docking technology. Originality/value This research can provide technical guidance and reference for spatial docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

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“…A human arm contains several antagonistic muscles and a complicated series–parallel mixed skeletal joint structure, while a single muscle comprises many skeletal anchors (Holzbaur et al , 2005). The human arm can rapidly, flexibly, safely and robustly complete complex operation tasks with high robustness, muscle nonlinearity and multimuscle redundancy (Qiao et al , 2021; Chen and Qiao, 2021; Zhong et al , 2021; Zhou et al , 2022; Qiao et al , 2022). Arm-musculoskeletal robots have been extensively studied owing to the flexibility of their skeletal joints (such as the absence of singular positions of shoulder-ball joints) and the variable stiffness control due to from multiple antagonistic muscles (Kawaharazuka et al , 2019; Asano et al , 2017; Kozuki et al , 2012; Wittmeier et al , 2013; Zhong et al , 2022).…”

Section: Introductionmentioning

confidence: 99%

Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm

Yuan

Fan

2023

RIA

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Purpose This study aims to propose a novel lightweight tendon-driven musculoskeletal arm (LTDM-arm) robot with a flexible series–parallel mixed skeletal joint structure and modularized artificial muscle system (MAMS). The proposed LTDM-arm exhibits human-like flexibility, safety and operational accuracy. In addition, to improve the safety and stability of the LTDM-arm, a control method is proposed to solve local artificial muscle overload accidents. Design/methodology/approach The proposed LTDM-arm comprises seven degrees of freedom skeletons, 15 MAMSs and various sensor systems (joint sensing, muscle tension sensing, visual sensing, etc.). It retains the morphology of a human skeleton (humerus, ulna and radius) and a simplified muscle configuration. This study proposes an input saturation control with full-state constraints to reduce local artificial muscle overload accidents caused by redundant muscle tension calculations. Findings 3D circular trajectory experiments were conducted to verify the stability of the control method and the flexibility of the LTDM-arm. The results showed that the average error of the muscle length was approximately 0.35 mm (0.38%), which indicates that the proposed control scheme can make the output follow the target trajectory while ensuring constraint satisfaction. Originality/value The human arm is capable of performing compliant operations rapidly, flexibly and robustly in unstructured environments. Existing musculoskeletal arm robots lack simulations of the full morphology of the human arm and are insufficient in dexterity. However, the flexibility and safety features of the proposed LTDM-arm were consistent with that of the human arm. Therefore, this study offers a new approach for investigating the advantages of the musculoskeletal system and the concepts of muscle control.

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Improving performance of robots using human-inspired approaches: a survey

Cited by 51 publications

References 215 publications

Actuation delay compensation of robots in semi-physical test

Actuation delay compensation of robots in semi-physical test

Stewart-inspired parallel spatial docking robot: design, analysis and experimental results

Design and input saturation control with full-state constraints of lightweight tendon-driven musculoskeletal arm

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