Approximation schemes for the restricted shortest path problem
Mathematics of Operations Research
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
An efficient algorithm for finding a path subject to two additive constraints
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Development environments for autonomous mobile robots: A survey
Autonomous Robots
A multi agent approach to vision based robot scavenging
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
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Many problems in robotics and AI, such as the find-path problem, call for optimal solutions that satisfy global constraints. The problem is complicated when the cost information is unknown, uncertain, or changing during execution of the solution. Such problems call for efficient re-planning during execution to account for the new information acquired. This paper presents a novel real-time algorithm, Constrained D* (CD*), that re-plans resolution optimal solutions subject to a global constraint. CD* performs a binary search on a weight parameter that sets the balance between the optimality and feasibility cost metrics. In each stage of the search, CD* uses Dynamic A* (D*) to update the weight selection for that stage. On average, CD* updates a feasible and resolution optimal plan in less than a second, enabling it to be used in a real-time robot controller. Results are presented for simulated problems. To the author's knowledge, CD* is the fastest algorithm to solve this class of problems.