Artificial Intelligence - Special volume on qualitative reasoning about physical systems
A logic-based calculus of events
New Generation Computing
Readings in qualitative reasoning about physical systems
Readings in qualitative reasoning about physical systems
Maintaining knowledge about temporal intervals
Readings in qualitative reasoning about physical systems
Qualitative-numeric simulation with Q3
Recent advances in qualitative physics
Making sense of virtual environments: action representation, grounding and common sense
Proceedings of the 12th international conference on Intelligent user interfaces
Efficient physics-based planning: sampling search via non-deterministic tactics and skills
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Comirit: Commonsense Reasoning by Integrating Simulation and Logic
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Grounding the lexical semantics of verbs in visual perception using force dynamics and event logic
Journal of Artificial Intelligence Research
Real-world robot navigation amongst deformable obstacles
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Self-explanatory simulations: an integration of qualitative and quantitative knowledge
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
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Performing everyday manipulation tasks successfully depends on the ability of autonomous robots to appropriately account for the physical behavior of task-related objects. Meaning that robots have to predict and consider the physical effects of their possible actions to take. In this work we investigate a simulation-based approach to naive physics temporal projection 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 temporal projection for naive physics problems should not be performed based on abstractions but rather based on detailed physical simulations. This idea is realized as a temporal projection 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. Within this paper, we describe the concept and implementation of the temporal projection system and present the example of an egg-cracking robot for demonstrating its feasibility.