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| research:naive-physics [2012/09/19 14:42] – created pmania | research:naive-physics [2023/09/18 12:52] (current) – cstoess | ||
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| - | ====== Naive Physics | + | ====== Naive Physics |
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| In this project, we investigate a simulation-based approach to naive physics prediction in the context of autonomous robot everyday manipulation. We identify the abstractions underlying typical first-order axiomatizations as the key obstacles for making valid naive physics predictions. We propose that naive physics reasoning should not be performed based on abstractions but rather based on detailed physical simulations. This idea is realized as a naive physics reasoning system for autonomous manipulation robots that translates naive physics problems into parametrized physical simulation tasks, that logs the data structures and states traversed in simulation, and translates the logged data back into symbolic time-interval-based first-order representations. | In this project, we investigate a simulation-based approach to naive physics prediction in the context of autonomous robot everyday manipulation. We identify the abstractions underlying typical first-order axiomatizations as the key obstacles for making valid naive physics predictions. We propose that naive physics reasoning should not be performed based on abstractions but rather based on detailed physical simulations. This idea is realized as a naive physics reasoning system for autonomous manipulation robots that translates naive physics problems into parametrized physical simulation tasks, that logs the data structures and states traversed in simulation, and translates the logged data back into symbolic time-interval-based first-order representations. | ||
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| === Project details === | === Project details === | ||
| - | Physical aspects about Eggs are modelled in an ontology: | + | Physical aspects about eggs are modelled in an ontology: |
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| === Simulation of a falling egg === | === Simulation of a falling egg === | ||
| - | The simulation is automatically configured by a scenario | + | The simulation is automatically configured by a scenario |
| ?- holds-tt(F1, | ?- holds-tt(F1, | ||
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| === Pouring pancake mix === | === Pouring pancake mix === | ||
| - | A pancake mix model made out of a big number of particles (in this case 400) is used to simulate | + | A pancake mix model made out of a big number of particles (in this case 400) is used to simulate |
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| === Turning a pancake === | === Turning a pancake === | ||
| - | A pancake model made of small particles connected by flexible joints is used an a simulation of a turning a pancake experiment, where the angle of the spatula is varied. The results of the experiment can be failure, if the pancake is not flipped, or success if it is. | + | A pancake model made of small particles connected by flexible joints is used as a simulation of a turning a pancake experiment, where the angle of the spatula is varied. The results of the experiment can be failure, if the pancake is not flipped, or success if it is. |
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| === Multiple pouring and turning results === | === Multiple pouring and turning results === | ||
| - | Pancake making experiments simulated in the Gazebo simulator. The PR2 robot model is pouring a pancake mix fluid composed of small particles on a pancake maker. During the pouring multiple results can be obtained by varying pouring parameters such as container height, angle and position and pouring time. After the liquid is poured, flexible joints are created between the particles on the pancake maker, to simulate the half cooked pancake. From the convex hull encompassing the particles a flexible texture mesh brings | + | Pancake making experiments simulated in the Gazebo simulator. The PR2 robot model is pouring a pancake mix fluid composed of small particles on a pancake maker. During the pouring, multiple results can be obtained by varying pouring parameters such as container height, angle, position, and pouring time. After the liquid is poured, flexible joints are created between the particles on the pancake maker to simulate the half cooked pancake. From the convex hull encompassing the particles a flexible texture mesh completes the pancake model. The resulted pancake is the flipped-on-the-other-side action which also can lead to different results. |
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| === Complete pancake making scenario === | === Complete pancake making scenario === | ||
| - | A complete pancake making experiment simulated in the Gazebo simulator. The PR2 robot model is retrieving the pancake mix container from the fridge, navigating to the counter and pouring a pancake mix fluid composed of small particles on a pancake maker. After the liquid is poured, flexible joints are created between the particles on the pancake maker, to simulate the half cooked pancake. From the convex hull encompassing the particles a flexible texture mesh brings | + | A complete pancake making experiment simulated in the Gazebo simulator. The PR2 robot model is retrieving the pancake mix container from the fridge, navigating to the counter, and pouring a pancake mix fluid composed of small particles on a pancake maker. After the liquid is poured, flexible joints are created between the particles on the pancake maker to simulate the half cooked pancake. From the convex hull encompassing the particles a flexible texture mesh completes the pancake model. At the end, the pancake is retrieved from the pancake maker and placed on a plate. Breakfast is served! |
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Prof. Dr. hc. Michael Beetz PhD
Head of Institute
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ai-office@cs.uni-bremen.de
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