The Concept of “Attractive Region in Environment” and its Application in High-Precision Tasks With Low-Precision Systems

Qiao, Hong; Wang, Min; Su, Jianhua; Jia, Shengxin; Li, Rui

doi:10.1109/tmech.2014.2375638

Cited by 120 publications

(58 citation statements)

References 38 publications

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“…As a matter of fact, some techniques for this problem rely on the high-precision sensory information feedback to minimize the measurement errors in the grasping process. However, it is worth mentioning that a key problem seems to be that the required minimum precision of the tasks has to be lesser than the precision of the sensory systems [46] . For the grasping problems, online grasping strategies in real-time designs are very difficult for adaptation of fast motion during the execution of the grasping task.…”

Section: Remaining Challengesmentioning

confidence: 99%

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Flexible robotic grasping strategy with constrained region in environment

Qiao

et al. 2017

Int. J. Autom. Comput.

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Grasping is a significant yet challenging task for the robots. In this paper, the grasping problem for a class of dexterous robotic hands is investigated based on the novel concept of constrained region in environment, which is inspired by the grasping operations of the human beings. More precisely, constrained region in environment is formed by the environment, which integrates a bio-inspired co-sensing framework. By utilizing the concept of constrained region in environment, the grasping by robots can be effectively accomplished with relatively low-precision sensors. For the grasping of dexterous robotic hands, the attractive region in environment is first established by model primitives in the configuration space to generate offline grasping planning. Then, online dynamic adjustment is implemented by integrating the visual sensory and force sensory information, such that the uncertainty can be further eliminated and certain compliance can be obtained. In the end, an experimental example of BarrettHand is provided to show the effectiveness of our proposed grasping strategy based on constrained region in environment.

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Section: Remaining Challengesmentioning

confidence: 99%

“…The theoretical framework of ARIE has been successfully applied in robotic areas related with tasks of grasping, assembly and other manufacturing processes to cope with uncertainties [46] .…”

Section: Definitionmentioning

confidence: 99%

Flexible robotic grasping strategy with constrained region in environment

Qiao

et al. 2017

Int. J. Autom. Comput.

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“…In the previous work, the definition and the generalized conditions of ARIE have been given and discussed (Qiao et al, 2014). As shown in Figure 1, if the initial state of the system is within the ARIE, it will finally converge to the stable point of this region, with the effect of a state independent input.…”

Section: Attractive Region In Environmentmentioning

confidence: 99%

The compliance of robotic hands – from functionality to mechanism

Qiao

2015

Assembly Automation

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2015),"Design of a novel dexterous robotic gripper for in-hand twisting and positioning within assembly automation", Assembly Automation, Vol. 35 Iss 3 pp. 259-268 http://dx.If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to introduce the physical structure and the control mechanism of human motor nervous system to the robotic system in a tentative manner to improve the compliance/flexibility/versatility of the robot. Design/methodology/approach -A brief review is focused on the concept of compliance, the compliance-based methods and the application of some compliance-based devices. Combined with the research on the physical structure and the control mechanism of human motor nervous system, a new drive structure and control method is proposed. Findings -Introducing the physical structure and the control mechanism of human motor nervous system can improve the compliance/flexibility/ versatility of the robot, without bringing in more complexity or inefficiency to the system, which helps in the assembly automation tasks. Originality/value -The proposed drive structure and control method are useful to build up a novel, low-cost robotic assembly automation system, which is easy to interact and cooperate with humans.

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“…Thanks to the rapid development of industrial automation, more and more work is now completed by machines [2]. Peg-hole assembly, flat panel parts assembly, and many other automatic assembly machines have been invented for this purpose [3,4].…”

Section: Introductionmentioning

confidence: 99%

Design of Demonstration-Driven Assembling Manipulator

et al. 2018

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Currently, a mechanical arm or manipulator needs to be programmed by humans in advance to define its motion trajectory before practical use. However, the programming is tedious and high-cost, which renders such manipulators unable to perform various different tasks easily and quickly. This article focuses on the design of a vision-guided manipulator without explicit human programming. The proposed demonstration-driven system mainly consists of a manipulator, control box, and camera. Instead of programming of the detailed motion trajectory, one only needs to show the system how to perform a given task manually. Based on internal object recognition and motion detection algorithms, the camera can capture the information of the task to be performed and generate the motion trajectories for the manipulator to make it copy the human demonstration. The movement of the joints of the manipulator is given by a trajectory planner in the control box. Experimental results show that the system can imitate humans easily, quickly, and accurately for common tasks such as sorting and assembling objects. Teaching the manipulator how to complete the desired motion can help eliminate the complexity of programming for motion control.

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The Concept of “Attractive Region in Environment” and its Application in High-Precision Tasks With Low-Precision Systems

Cited by 120 publications

References 38 publications

Flexible robotic grasping strategy with constrained region in environment

Flexible robotic grasping strategy with constrained region in environment

The compliance of robotic hands – from functionality to mechanism

Design of Demonstration-Driven Assembling Manipulator

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