Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Explaining and repairing plans that fail
Artificial Intelligence
Theoretical Computer Science
A validation-structure-based theory of plan modification and reuse
Artificial Intelligence
Dynamic map building for an autonomous mobile robot
International Journal of Robotics Research
A note on the combinatorial structure of the visibility graph in simple polygons
Theoretical Computer Science - Special issue on design and analysis of geometrical algorithms for robot motion planning and vision
An incremental algorithm for a generalization of the shortest-path problem
Journal of Algorithms
Sensor based motion planning: the hierarchical generalized Voronoi graph
Sensor based motion planning: the hierarchical generalized Voronoi graph
How to learn an unknown environment. I: the rectilinear case
Journal of the ACM (JACM)
Map learning and high-speed navigation in RHINO
Artificial intelligence and mobile robots
Learning to learn
Piecemeal graph exploration by a mobile robot
Information and Computation
Exploring unknown undirected graphs
Journal of Algorithms
Fully dynamic algorithms for maintaining shortest paths trees
Journal of Algorithms
Exploring Unknown Environments
SIAM Journal on Computing
Planning and Learning by Analogical Reasoning
Planning and Learning by Analogical Reasoning
Multiagent Mission Specification and Execution
Autonomous Robots
Multistrategy Adaptive Path Planning
IEEE Expert: Intelligent Systems and Their Applications
On a Simple Depth-First Search Strategy for Exploring Unknown Graphs
WADS '97 Proceedings of the 5th International Workshop on Algorithms and Data Structures
Collaborative Multi-robot Localization
KI '99 Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Exploration of Unknown Environments by a Mobile Robot
Intelligent Autonomous Systems 2, An International Conference
On Plan Adaption through Planning Graph Analysis
AI*IA '99 Proceedings of the 6th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Speeding up the calculation of heuristics for heuristic search-based planning
Eighteenth national conference on Artificial intelligence
SFCS '90 Proceedings of the 31st Annual Symposium on Foundations of Computer Science
A domain-independent algorithm for plan adaptation
Journal of Artificial Intelligence Research
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Real-time map building and navigation for autonomous robots inunknown environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Mobile robots often have to replan as their knowledge of the world changes. Lifelong planning is a paradigm that allows them to replan much faster than with complete searches from scratch, yet finds optimal solutions. To demonstrate this paradigm, we apply it to Greedy Mapping, a simple sensor-based planning method that always moves the robot from its current cell to a closest cell with unknown blockage status, until the terrain is mapped. Greedy Mapping has a small mapping time, makes only action recommendations and can thus coexist with other components of a robot architecture that also make action recommendations, and is able to take advantage of prior knowledge of parts of the terrain (if available). We demonstrate how a robot can use our lifelong-planning version of A* to repeatedly determine a shortest path from its current cell to a closest cell with unknown blockage status. Our experimental results demonstrate the advantage of lifelong planning for Greedy Mapping over other search methods. Similar results had so far been established only for goal-directed navigation in unknown terrain.