Optimized adaptive tracking control for an underactuated vibro-driven capsule system

Liu, Pengcheng; Yu, Hongnian; Cang, Shuang

doi:10.1007/s11071-018-4458-9

Cited by 55 publications

(19 citation statements)

References 42 publications

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“…As presented above, these bio-inspired motion perception models could be ideal choices for design of neuromorphic vision sensors as a future trend of hardware realisation of visual processing. Furthermore, these low-energy and miniaturised visual sensing modalities would be able to incorporated in some control systems for much broader applications in robotics, such as the underactuated systems [127], and corresponding bio-inspired robot applications like the vibro-driven robot [126].…”

Section: Hardware Realisation Of Insect Motion Perception Modelsmentioning

confidence: 99%

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Wang

et al. 2019

Artificial Life

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Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging and so forth. A good number of motion detectors have been identified in the insects' visual pathways.Computational modelling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research of insects' visual systems in the literature. These motion perception models or neural networks comprise the looming sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation sensitive neural systems of direction selective neurons (DSNs) in fruit flies, bees and locusts, as well as the small target motion detectors (STMDs) in dragonflies and hover flies. We also review the applications of these models to robots and vehicles. Through these modelling studies, we summarise the methodologies that generate different direction and size selectivity in motion perception. At last, we discuss about multiple systems integration and hardware realisation of these bio-inspired motion perception models.

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Section: Hardware Realisation Of Insect Motion Perception Modelsmentioning

confidence: 99%

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Wang

et al. 2019

Artificial Life

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“…Underactuated mechanical systems (UMSs) are rapidly growing research fields that combine control and robotics societies [1][2][3][4][5][6][7][8]. They have extensive applications such as UAVs, underground vehicles, spacecraft, humanoid robots and vibro-driven robots [9][10][11][12]. UMSs have more degrees-of-freedom (DOF) n than independent control inputs m; thus, (n-m) DOF are not directly controllable, which characterize the nature of underactuation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural network tracking control for underactuated systems with matched and mismatched disturbances

2019

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This paper studies neural network-based tracking control of underactuated systems with unknown parameters and with matched and mismatched disturbances. Novel adaptive control schemes are proposed with the utilization of multi-layer neural networks, adaptive control and variable structure strategies to cope with the uncertainties containing approximation errors, unknown base parameters and time-varying matched and mismatched external disturbances. Novel auxiliary control variables are designed to establish the controllability of the non-collocated subset of the underactuated systems. The approximation errors and the matched and mismatched external disturbances are efficiently counteracted by appropriate design of robust compensators. Stability and convergence of the time-varying reference trajectory are shown in the sense of Lyapunov. The parameter updating laws for the designed control schemes are derived using the projection approach to reduce the tracking error as small as desired. Unknown dynamics of the

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“…Effective utilizations of flexible elements into the robotic locomotion have attracted significant interests in robotics and control communities. The motivations are diverse, for instance, to build up safer interactions with humans [1,2], to improve the model accuracy of the robotic systems [3,4], to achieve higher level of manoeuvrability, high bandwidth mechanical compliance, flexibility, agility, controllability, adaptability, and efficacy in fulfilling large scope of tasks in unstructured and hazardous environment [5][6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A self-propelled robotic system with a visco-elastic joint: dynamics and motion analysis

Liu

Huda

Tang

et al. 2019

Engineering with Computers

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This paper studies the dynamics and motion generation of a self-propelled robotic system with a visco-elastic joint. The system is underactuated, legless and wheelless, and has potential applications in environmental inspection and operation in restricted space which are inaccessible to human beings, such as pipeline inspection, medical assistance and disaster rescues. Locomotion of the system relies on the stick-slip effects, which interacts with the frictional force at the surface in contact. The nonlinear robotic model utilizes combined tangential-wise and normal-wise vibrations for underactuated locomotion, which features a generic significance for the studies on self-propelled systems. To identify the characteristics of the visco-elastic joint and shed light on the energy efficacy, parameter dependences on stiffness and damping coefficients are thoroughly analysed. Our studies demonstrate that dynamic behaviour of the self-propelled system is mainly periodic and desirable forward motion is achieved via identification of the variation laws of the control parameters and elaborate selection of the stiffness and damping coefficients. A motion generation strategy is developed, and an analytical two-stage motion profile is proposed based on the system response and dynamic constraint analysis, followed by a parameterization procedure to optimally generate the trajectory. The proposed method provides a novel approach in generating self-propelled locomotion, and designing and computing the visco-elastic parameters for energy efficacy. Simulation results are presented to demonstrate the effectiveness and feasibility of the proposed model and motion generation approach.

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Optimized adaptive tracking control for an underactuated vibro-driven capsule system

Cited by 55 publications

References 42 publications

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Adaptive neural network tracking control for underactuated systems with matched and mismatched disturbances

A self-propelled robotic system with a visco-elastic joint: dynamics and motion analysis

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