# More knowledge on the table: Planning with space, time and resources for robots

@article{Mansouri2014MoreKO,
title={More knowledge on the table: Planning with space, time and resources for robots},
author={Masoumeh Mansouri and Federico Pecora},
journal={2014 IEEE International Conference on Robotics and Automation (ICRA)},
year={2014},
pages={647-654}
}
• Published 29 September 2014
• Computer Science
• 2014 IEEE International Conference on Robotics and Automation (ICRA)
AI-based solutions for robot planning have so far focused on very high-level abstractions of robot capabilities and of the environment in which they operate. However, to be useful in a robotic context, the model provided to an AI planner should afford both symbolic and metric constructs; its expressiveness should not hinder computational efficiency; and it should include causal, spatial, temporal and resource aspects of the domain. We propose a planner grounded on well-founded constraint-based…

## Figures from this paper

Hierarchical Hybrid Planning in a Mobile Service Robot
• Computer Science
KI
• 2015
The straightforward integration of different kinds of knowledge for causal, temporal and resource knowledge as well as knowledge provided by an external path planner is demonstrated, resulting in an HTN planner able to handle very rich domain knowledge.
Online task merging with a hierarchical hybrid task planner for mobile service robots
• Computer Science
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• 2015
The planner CHIMP is introduced, which is based on meta-CSP planning to represent the hybrid plan space and uses hierarchical planning as the strategy for cutting efficiently through this space.
Temporal and Hierarchical Models for Planning and Acting in Robotics
It is argued that a successful integration with a robotic system requires the planner to have capacities for both temporal and hierarchical reasoning, and a model for temporal planning unifying the generative and hierarchical approaches is presented.
Hierarchische hybride Planung für mobile Roboter
This thesis presents the hierarchical hybrid planner CHIMP which combines the advantages of hierarchical planning and hybrid planning with different forms of knowledge as a MetaCSP [28, 104].
Introducing a Human-like Planner for Reaching in Cluttered Environments
• Computer Science
• 2020
This work uses virtual reality to generate data from human participants whilst they reached for objects on a cluttered table top and devised a qualitative representation of the task space to abstract human decisions, irrespective of the number of objects in the way, which outperforms a state-of-the-art standard trajectory optimisation algorithm.
Human-like Planning for Reaching in Cluttered Environments
• Computer Science
2020 IEEE International Conference on Robotics and Automation (ICRA)
• 2020
The human-like planner outperformed a state-of-the-art standard trajectory optimisation algorithm, and was able to generate effective strategies for rapid planning- irrespective of the number of obstacles in the environment.
Integrating physics-based prediction with Semantic plan Execution Monitoring
• Computer Science
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• 2015
An integrated system that uses a physics-based simulation to predict robot action results and durations, combined with a Hierarchical Task Network (HTN) planner and semantic execution monitoring and improves on state-of-the-art AI plan-based systems by feeding simulated prediction results back into the execution system.
PLATINUm: A New Framework for Planning and Acting
• Computer Science
AI*IA
• 2017
The paper surveys the capabilities of this new planning system that has been recently deployed in a manufacturing scenario to support Human-Robot Collaboration.
Timeline-based Planning and Execution with Uncertainty: Theory, Modeling Methodologies and Practice
The objective of this work is to investigate the timeline-based approach to planning by addressing several aspects ranging from the semantics of the related planning concepts to the modeling and solving techniques.
Is Model-Based Robot Programming a Mirage? A Brief Survey of AI Reasoning in Robotics
• F. Pecora
• Computer Science
KI - Künstliche Intelligenz
• 2014
Forty-eight years after the first AI-driven robot, this article provides an updated perspective on the successes and challenges which lie at the intersection of AI and Robotics.

## References

SHOWING 1-10 OF 35 REFERENCES
A representation for spatial reasoning in robotic planning
• Computer Science
IROS 2013
• 2013
This paper proposes a knowledge representation and reasoning technique, grounded on well-established spatial calculi, for combining qualitative and metricknowledge and obtaining solutions expressed in actionablemetric terms.
When robots are late: Configuration planning for multiple robots with dynamic goals
• Computer Science
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
• 2013
An approach to closed-loop planning capable of generating configuration plans, i.e., action plans for multirobot systems which specify the causal, temporal, resource and information dependencies between individual sensing, computation, and actuation components is proposed.
Taking Into Account Geometric Constraints for Task-oriented Motion Planning
• Computer Science
• 2009
The classical planning formalism is proposed to be extended in order to model actions with geometric preconditions and a constraint satisfaction method is proposed that aims at defining a destination attitude for motion planning.
Guiding the Generation of Manipulation Plans by Qualitative Spatial Reasoning
• Computer Science
Spatial Cogn. Comput.
• 2011
This article presents an approach that generates heuristics for the probabilistic sampling strategy from spatial plans that abstract from concrete metric data and discusses how such formalisms and constraint-based reasoning methods can be applied to approximate geometrically feasible motions.
Parameterizing actions to have the appropriate effects
• Computer Science
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems
• 2011
A lightweight and fast reasoning system that integrates qualitative and quantitative reasoning based on Prolog that allows for the generation of action parameters such as put down locations under the constraints of the current and future actions in real time is shown.
Ontology Based Spatial Planning for Human-Robot Interaction
• Computer Science
2010 17th International Symposium on Temporal Representation and Reasoning
• 2010
This paper proposes here an ontology called \textit{Space Ontology} as a spatial knowledge representation and reasoning system, and shows how this type of knowledge can be profitably used for task planning.
Spatial Reasoning for Real-time Robotic Manipulation
• Computer Science
2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
• 2006
The experimental results show the feasibility of using graphics hardware for manipulative robotic tasks and further its performance gain in real-time manipulation.
Spatial Representation and Reasoning for Human-Robot Collaboration
• Psychology
AAAI
• 2007
The cognitive modeling system, ACT-R, is used with an added spatial module to support the robot's spatial reasoning and its integration of metric, symbolic, and cognitive layers of spatial representation and reasoning for its individual and team behavior.
A temporal logic-based planning and execution monitoring framework for unmanned aircraft systems
• Computer Science
Autonomous Agents and Multi-Agent Systems
• 2009
This article presents a temporal logic-based task planning and execution monitoring framework and its integration into a fully deployed rotor-based unmanned aircraft system developed in the laboratory, and shows how formulas in the same logic can be used to specify the desired behavior of the system and its environment.
Constraint propagation on interval bounds for dealing with geometric backtracking
• Computer Science
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
• 2012
This paper uses intervals to represent geometric configurations, and constraint propagation techniques to shrink these intervals according to the geometric constraints of the problem, and reports experiments that show how the search space is reduced.