Stable transport of assemblies by pushing

Bernheisel, J.D.; Lynch, Kevin

doi:10.1109/tro.2006.875488

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…Stable transport of assemblies of parts without grasping has been studied by Bernheisel and Lynch [4], [5], who analyzed the stable transport of planar arrangements of parts by pushing motions. They identify force balance conditions that guarantee an assembly of parts stays assembled as it is pushed.…”

Section: A Stability Analysismentioning

confidence: 99%

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The Influence of Motion Paths and Assembly Sequences on the Stability of Assemblies

Rakshit

Akella

2015

IEEE Trans. Automat. Sci. Eng.

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In this paper, we present an approach for the stability analysis of mechanical part disassembly considering part motion in the presence of physical forces such as gravity and friction. Our approach uses linear complementarity to analyze stability as parts are moved out of the assembly. As each part is removed from the assembly along a specified path during disassembly, we compute the contact forces between parts in the remaining assembly; positive contact forces throughout the disassembly process imply the disassembly sequence is stable (since the parts remain in contact with one another). However, if the part that is being taken out induces motion of other parts in the remaining subassembly, we conclude the disassembly sequence is unstable. Thus, we are able to simulate the entire disassembly considering physical forces and part motion, which has not previously been done. We then show the influence of part motion on stable disassembly. In contrast to prior work on disassembly that has focused either on planning part motions based on only geometric constraints, or on analyzing the stability of an assembly without considering part motions, we explore the relation between part motion and the selection of stable disassembly sequences in 2-D and 3-D. We establish conditions that characterize path-dependent assemblies, where motion paths can play a significant role in stable disassembly. Since we track the motion of all parts in an assembly, instability inducing motions can be identified and prevented by introducing appropriate fixtures by selecting alternative disassembly sequences or by changing the motion paths. We extend the stability analysis for single part disassembly to stability analysis of subassembly disassembly. We additionally show that in the presence of friction, assembly and disassembly can be noninvertible.Note to Practitioners-Maintaining the stability of an assembly as assembly or disassembly proceeds is critical during product assembly, repair, and maintenance. While fixtures can ensure stability, they add cost and restrict access for parts and tools. We show that the stability of the assembly can depend on the paths taken by the parts, and present an approach for selecting paths that ensure stability from among the geometrically feasible paths. The main application is in assembly and disassembly planning for reducing the fixturing requirements and in planning assembly motions that do not cause instability. The results will also be useful in designing disassembly operations during maintenance or repair, when it may not be possible to fixture all parts. The stability analysis can also be used by assistive robots in domestic environments for tasks like Manuscript stacking objects and for safe removal of collapsed structures after disasters such as earthquakes.

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Section: A Stability Analysismentioning

confidence: 99%

“…Using the Stewart-Trinkle model, we formulate the motion path stability problem as a linear complementarity problem as follows: (5) where superscript indicates value at time . ,…”

Section: A Motion Stability Problemmentioning

confidence: 99%

The Influence of Motion Paths and Assembly Sequences on the Stability of Assemblies

Rakshit

Akella

2015

IEEE Trans. Automat. Sci. Eng.

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“…Using Goyal's models [8] (or simplifications of it), stable pushing tasks have been accomplished [12][13] [14]. These solutions have in common that they try to exploit the friction between the actuator and the objects to achieve naturally stable pushing; then they use a motion planner to guide the objects to the desired goal.…”

Section: Related Workmentioning

confidence: 99%

Fast adaptation for effect-aware pushing

Ruiz-Ugalde

Cheng

Beetz

2011

2011 11th IEEE-RAS International Conference on Humanoid Robots

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Abstract-In order to produce robots that are more capable of skilled manipulation tasks, they must learn meaningful knowledge of how objects behave to external stimulus. With this knowledge a robot can predict the outcome of an action, control the object to serve a particular purpose, and together with reasoning, create or modify robot plans. In this paper we 1) build a mathematical compact model for planar sliding motion of an object, 2) show how a robot acquires the parameters of such a model; then how this is used to 3) predict pushing actions; and 4) to move an object from any 1 position and orientation to another.

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“…Approaches in this category assume that an accurate geometric model of the manipulated object is available and devise manipulation plans based on this model. These manipulation planners address various flavors of manipulation, including grasping and in-hand manipulation [24], manipulation with sliding contacts [26], non-prehensile manipulation [1,14], and gross motion planning for manipulation [21]. In contrast to these approaches, we focus on problems for which accurate models are not available.…”

Section: Related Workmentioning

confidence: 99%

Learning to Manipulate Articulated Objects in Unstructured Environments Using a Grounded Relational Representation

Katz¹,

Pyuro²,

Brock³

2008

Robotics: Science and Systems IV

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Abstract-We introduce a learning-based approach to manipulation in unstructured environments. This approach permits autonomous acquisition of manipulation expertise from interactions with the environment. The resulting expertise enables a robot to perform effective manipulation based on partial state information. The manipulation expertise is represented in a relational state representation and learned using relational reinforcement learning. The relational representation renders learning tractable by collapsing a large number of states onto a single, relational state. The relational state representation is carefully grounded in the perceptual and interaction skills of the robot. This ensures that symbolically learned knowledge remains meaningful in the physical world. We experimentally validate the proposed learning approach on the task of manipulating an articulated object to obtain a model of its kinematic structure. Our experiments demonstrate that the manipulation expertise acquired by the robot leads to substantial performance improvements. These improvements are maintained when experience is applied to previously unseen objects.

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Stable transport of assemblies by pushing

Cited by 14 publications

References 20 publications

The Influence of Motion Paths and Assembly Sequences on the Stability of Assemblies

The Influence of Motion Paths and Assembly Sequences on the Stability of Assemblies

Fast adaptation for effect-aware pushing

Learning to Manipulate Articulated Objects in Unstructured Environments Using a Grounded Relational Representation

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