Bidirectional Human–Robot Bimanual Handover of Big Planar Object With Vertical Posture

He, Wei; Li, Jiashu; Yan, Zichen; Chen, Fei

doi:10.1109/tase.2020.3043480

Cited by 16 publications

(5 citation statements)

References 69 publications

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“…(2) Recently, some important results on systems with stochastic noise, incomplete measurements, codingdecoding mechanisms, and protocol scheduling have been achieved; see [52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67] and other papers.…”

Section: Discussionmentioning

confidence: 99%

Adaptive Event‐Triggered Finite‐Time Tracking of Output‐Constrained High‐Order Nonlinear Systems with Time‐Varying Powers

Liu

2022

Complexity

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This paper studies the adaptive event-triggered finite-time tracking of output-constrained high-order nonlinear systems with time-varying powers. Due to the presence of multiple unknown powers and the consideration of event-triggered control, all the existing control methods of output-constrained nonlinear systems are inapplicable. By introducing nonlinear mappings, finite-time performance functions, and low-power and high-power terms into adding a power integrator technique and the relative threshold strategy, an adaptive state-feedback controller is designed to eliminate the effects caused by the output constraint and time-varying powers. It is proved that all the closed-loop signals are bounded, the asymmetric time-varying output constraint is not violated, and the tracking error converges to a prescribed arbitrarily small region around zero in a preassigned finite time. Furthermore, the Zeno phenomenon can be avoided. Two simulation examples demonstrate the effectiveness of this control scheme.

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Section: Discussionmentioning

confidence: 99%

Adaptive Event‐Triggered Finite‐Time Tracking of Output‐Constrained High‐Order Nonlinear Systems with Time‐Varying Powers

Liu

2022

Complexity

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“…Several recent works have already developed partial solutions regarding the humanrobot object handover procedure [132][133][134], some of which are inspired by human strategies [83,103,135,136]. However, none of them provides a generic solution for a human adaptive system, where the exchange of objects occurs fluently, similarly to what happens between two humans, for the robot to become a much more reliable and useful machine.…”

Section: Open Research Questions In Object Handovermentioning

confidence: 99%

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics

Castro

Silva

Santos

2021

Sensors

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Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of the most significant subjects for human-life improvement.The ultimate goal is to achieve physical interaction, where handing over an object plays a crucial role for an effective task accomplishment. Considerable research work had been developed in this particular field in recent years, where several solutions were already proposed. Nonetheless, some particular issues regarding Human-Robot Collaboration still hold an open path to truly important research improvements. This paper provides a literature overview, defining the HRC concept, enumerating the distinct human-robot communication channels, and discussing the physical interaction that this collaboration entails. Moreover, future challenges for a natural and intuitive collaboration are exposed: the machine must behave like a human especially in the pre-grasping/grasping phases and the handover procedure should be fluent and bidirectional, for an articulated function development. These are the focus of the near future investigation aiming to shed light on the complex combination of predictive and reactive control mechanisms promoting coordination and understanding. Following recent progress in artificial intelligence, learning exploration stand as the key element to allow the generation of coordinated actions and their shaping by experience.

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“…While existing research primarily focuses on handovers of objects that require a unimanual grasp [16,13,11,9], the need for bimanual handovers arises in scenarios involving large rigid items, deformable objects, spherical objects, and cultural etiquette. Surprisingly, there is limited research on robot controllers for bimanual handovers [17,8], and the existing approaches lack the generation of human-like robot motions.…”

Section: Introductionmentioning

confidence: 99%

Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers

Göksu,

De Almeida Correia,

Prasad

et al. 2024

Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction

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Bidirectional Human–Robot Bimanual Handover of Big Planar Object With Vertical Posture

Cited by 16 publications

References 69 publications

Adaptive Event‐Triggered Finite‐Time Tracking of Output‐Constrained High‐Order Nonlinear Systems with Time‐Varying Powers

Adaptive Event‐Triggered Finite‐Time Tracking of Output‐Constrained High‐Order Nonlinear Systems with Time‐Varying Powers

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics

Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers

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