Planning of graspless manipulation by a multifingered robot hand

Maeda, Yusuke; Arai, Tamio

doi:10.1163/156855305323383776

Cited by 30 publications

(16 citation statements)

References 11 publications

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“…The results were tested in simulations that were constructed in Box2D. We compared the performance of our approach to that of a "combined" planner (similar in structure to those of Maeda et al [16,17]) that follows an object contact-state path but plans for both and robot contacts at the same time.…”

Section: Implementation and Resultsmentioning

confidence: 99%

“…The line of work most closely related to our own is by Maeda and Arai; they have successfully demonstrated non-prehensile manipulation planning with multiple robot contacts across multiple contact states [16,17]. Initially, they assumed a planar environment and that the contact state graph was given; they discretized the combined configuration space of the object and the robot hands in each contact state, connecting poses for transits and transfers.…”

Section: Related Workmentioning

confidence: 99%

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Hierarchical planning for multi-contact non-prehensile manipulation

Lee

Lozano-Pérez

Kaelbling

2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Manipulation planning involves planning the combined motion of objects in the environment as well as the robot motions to achieve them. In this paper, we explore a hierarchical approach to planning sequences of non-prehensile and prehensile actions. We subdivide the planning problem into three stages (object contacts, object poses and robot contacts) and thereby reduce the size of search space that is explored. We show that this approach is more efficient than earlier strategies that search in the combined robot-object configuration space directly.

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Section: Implementation and Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Hierarchical planning for multi-contact non-prehensile manipulation

Lee

Lozano-Pérez

Kaelbling

2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…[17]. Maeda et al proposed a method of planning of general graspless manipulation by multifingered robot hands [18]. These papers discuss methods of varying the position and orientation of the objects as they remain in contact with aspects of the environment, by tumbling, pivoting, or tilting them instead of grasping them.…”

Section: Related Workmentioning

confidence: 99%

Realization of heavy object transportation by mobile robots using handcarts and outrigger

et al. 2016

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In this paper, we have dealt with the problem to transport large heavy objects using a group of small mobile robots. Generally, payload of the robot, the maximum weight of the object that the robot can operate, is very small and they cannot transport heavy objects with standard coordinated grasping methodology. This paper considers a method of transporting an object using handcarts by tilting the object to load it on the handcarts. To resolve the problem of avoiding overturning of the object by the robots and sliding of the handcart while tilting the object, an outrigger device is used to prevent the first problem of tilting, and a handcart locking device is used to prevent the second problem of sliding. As both devices need to be used only when necessary, a mechanism that can fix and release the devices according to situations is newly designed. Two robots were trial fabricated: an object-tilting robot equipped with an outrigger mechanism and a handcart transport robot to handle the handcarts. Both robots are smaller than 0.6 m × 0.6 m with payload of 2.5 kg. They are equipped with a handcart mechanism that can be locked and unlocked. The use of the coordination and lock mechanisms by these robots has realized transport of objects approximately 1 m high and weighing approximately 35 kg and demonstrated the effectiveness of the proposed system in a real-world environment where robot mechanism errors, mobility errors, and observation errors occur.

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“…The manipulated object is in contact with not only the robot but also with the environment. Moreover, graspless manipulation may be irreversible (Maeda et al, 2004;Maeda and Arai, 2005;Miyazawa et al, 2005). Nonprehensile manipulation methods are majorly divided into two different categories; quasi-static and dynamic manipulation methods.…”

Section: Introductionmentioning

confidence: 99%

An algorithm for dynamic object manipulation by a flexible link robot

Tarvirdizadeh

Alipour

Hadi

2016

Engineering Computations

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Purpose -The purpose of this paper is to focus on an online closed-loop (CL) approach for performing dynamic object manipulation (DOM) by a flexible link manipulator. Design/methodology/approach -Toward above goal, a neural network and optimal control are integrated in a closed-loop structure, to achieve a robust control for online DOM applications. Additionally, an elegant novel numerical solution method will be developed which can handle the split boundary value problem resulted from DOM mission requirements for a wide range of boundary conditions. Findings -The obtained simulation results reveal the effectiveness of both proposed innovative numerical solution technique and control structure for online object manipulation purposes using flexible manipulators. Originality/value -The object manipulation problem has previously been studied, however, for the first time its accomplishment by flexible link manipulators was addressed just in offline form considering an open-loop control structure (Tarvirdizadeh and Yousefi-Koma, 2012). As an extension of Tarvirdizadeh and Yousefi-Koma (2012), the current research, consequently, focusses on a numerical solution and a CL approach for performing DOM by a flexible link manipulator.

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Planning of graspless manipulation by a multifingered robot hand

Cited by 30 publications

References 11 publications

Hierarchical planning for multi-contact non-prehensile manipulation

Hierarchical planning for multi-contact non-prehensile manipulation

Realization of heavy object transportation by mobile robots using handcarts and outrigger

An algorithm for dynamic object manipulation by a flexible link robot

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