Towards A Relational Approach For Tool Creation By Robots

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence ◽

10.24963/ijcai.2017/770 ◽

2017 ◽

Author(s):

Handy Wicaksono

Keyword(s):

3D Printing ◽

Past Experience ◽

Complex Task ◽

Relational Approach

Like a human, a robot may benefit from being able to use a tool to solve a complex task. When an appropriate tool is not available, a very useful ability for a robot would be to create a novel one based on its past experience. With the advent of inexpensive 3D printing, it is now possible to give robots such an ability, at least to create simple tools. We propose a method for learning how to use an object as a tool and, if needed, to design and construct a new tool.

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A cognitive robot equipped with autonomous tool innovation expertise

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v10i2.pp2200-2207 ◽

2020 ◽

Vol 10 (2) ◽

pp. 2200

Author(s):

Handy Wicaksono ◽

Claude Sammut

Keyword(s):

3D Printing ◽

Tool Use ◽

General Model ◽

Search Space ◽

Complex Task ◽

Trial And Error ◽

Constraint Solver ◽

Action Model

Like a human, a robot may benefit from being able to use a tool to solve a complex task. When an appropriate tool is not available, a very useful ability for a robot is to create a novel one based on its experience. With the advent of inexpensive 3D printing, it is now possible to give robots such an ability, at least to create simple tools. We proposed a method for learning how to use an object as a tool and, if needed, to design and construct a new tool. The robot began by learning an action model of tool use for a PDDL planner by observing a trainer. It then refined the model by learning by trial and error. Tool creation consisted of generalising an existing tool model and generating a novel tool by instantiating the general model. Further learning by experimentation was performed. Reducing the search space of potentially useful tools could be achieved by providing a tool ontology. We then used a constraint solver to obtain numerical parameters from abstract descriptions and use them for a ready-to-print design. We evaluated our system using a simulated and a real Baxter robot in two cases: hook and wedge. We found that our system performs tool creation successfully.

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Above and beyond the content: Feelings influence mental simulations

Behavioral and Brain Sciences ◽

10.1017/s0140525x19003108 ◽

2020 ◽

Vol 43 ◽

Author(s):

Kellen Mrkva ◽

Luca Cian ◽

Leaf Van Boven

Keyword(s):

Mental Representation ◽

Mental Simulation ◽

Past Experience ◽

Prediction Errors

Abstract Gilead et al. present a rich account of abstraction. Though the account describes several elements which influence mental representation, it is worth also delineating how feelings, such as fluency and emotion, influence mental simulation. Additionally, though past experience can sometimes make simulations more accurate and worthwhile (as Gilead et al. suggest), many systematic prediction errors persist despite substantial experience.

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Statistics and parallaxes

International Astronomical Union Colloquium ◽

10.1017/s0252921100073875 ◽

1978 ◽

Vol 48 ◽

pp. 7-29

Author(s):

T. E. Lutz

Keyword(s):

Experimental Design ◽

Statistical Methods ◽

Review Paper ◽

Systematic Errors ◽

Past Experience ◽

Random Errors ◽

Trigonometric Parallaxes ◽

Systematic And Random Errors

This review paper deals with the use of statistical methods to evaluate systematic and random errors associated with trigonometric parallaxes. First, systematic errors which arise when using trigonometric parallaxes to calibrate luminosity systems are discussed. Next, determination of the external errors of parallax measurement are reviewed. Observatory corrections are discussed. Schilt’s point, that as the causes of these systematic differences between observatories are not known the computed corrections can not be applied appropriately, is emphasized. However, modern parallax work is sufficiently accurate that it is necessary to determine observatory corrections if full use is to be made of the potential precision of the data. To this end, it is suggested that a prior experimental design is required. Past experience has shown that accidental overlap of observing programs will not suffice to determine observatory corrections which are meaningful.

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Life Beyond 1MeV

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s1431927600000118 ◽

1980 ◽

Vol 38 ◽

pp. 30-33

Author(s):

K.H. Westmacott

Keyword(s):

Electron Microscopy ◽

Past Experience ◽

The Other ◽

Good Case ◽

Other Hand ◽

The U.S

Life beyond 1MeV – like life after 40 – is not too different unless one takes advantage of past experience and is receptive to new opportunities. At first glance, the returns on performing electron microscopy at voltages greater than 1MeV diminish rather rapidly as the curves which describe the well-known advantages of HVEM often tend towards saturation. However, in a country with a significant HVEM capability, a good case can be made for investing in instruments with a range of maximum accelerating voltages. In this regard, the 1.5MeV KRATOS HVEM being installed in Berkeley will complement the other 650KeV, 1MeV, and 1.2MeV instruments currently operating in the U.S. One other consideration suggests that 1.5MeV is an optimum voltage machine – Its additional advantages may be purchased for not much more than a 1MeV instrument. On the other hand, the 3MeV HVEM's which seem to be operated at 2MeV maximum, are much more expensive.

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