DD* Lite: Efficient Incremental Search with State Dominance
نویسندگان
چکیده
This technical report presents DD* Lite, an efficient incremental search algorithm for problems that can capitalize on state dominance. Dominance relationships between nodes are used to prune graphs in search algorithms. Thus, exploiting state dominance relationships can considerably speed up search problems in large state spaces, such as mobile robot path planning considering uncertainty, time, or energy constraints. Incremental search techniques are useful when changes can occur in the search graph, such as when re-planning paths for mobile robots in partially known environments. While algorithms such as D* and D* Lite are very efficient incremental search algorithms, they cannot be applied as formulated to search problems in which state dominance is used to prune the graph. DD* Lite extends D* Lite to seamlessly support reasoning about state dominance. It maintains the algorithmic simplicity and incremental search capability of D* Lite, while resulting in orders of magnitude increase in search efficiency in large state spaces with dominance. We illustrate the efficiency of DD* Lite with simulation results from applying the algorithm to a path planning problem with time and energy constraints. We also prove that DD* Lite is sound, complete, optimal, and efficient.
منابع مشابه
Reusing Previously Found A* Paths for Fast Goal-Directed Navigation in Dynamic Terrain
Generalized Adaptive A* (GAA*) is an incremental algorithm that replans using A* when solving goal-directed navigation problems in dynamic terrain. Immediately after each A* search, it runs an efficient procedure that updates the heuristic values of states that were just expanded by A*, making them more informed. Those updates allow GAA* to speed up subsequent A* searches. Being based on A*, it...
متن کاملTruncated Incremental Search: Faster Replanning by Exploiting Suboptimality
Incremental heuristic searches try to reuse their previous search efforts whenever these are available. As a result, they can often solve a sequence of similar planning problems much faster than planning from scratch. State-of-the-art incremental heuristic searches such as LPA*, D* and D* Lite all work by propagating cost changes to all the states on the search tree whose gvalues (the costs of ...
متن کاملMoving target D* Lite
Incremental search algorithms, such as Generalized FringeRetrieving A* and D* Lite, reuse search trees from previous searches to speed up the current search and thus often find cost-minimal paths for series of similar search problems faster than by solving each search problem from scratch. However, existing incremental search algorithms have limitations. For example, D* Lite is slow on moving t...
متن کاملGeneralized Adaptive A*
Agents often have to solve series of similar search problems. Adaptive A* is a recent incremental heuristic search algorithm that solves series of similar search problems faster than A* because it updates the h-values using information from previous searches. It basically transforms consistent hvalues into more informed consistent h-values. This allows it to find shortest paths in state spaces ...
متن کاملAvoiding Unnecessary Calculations in Robot Navigation
For solving problems of robot navigation over unknown and changing terrain, many algorithms have been invented. For example, D* Lite, which is a dynamic, incremental search algorithm, is the most successful one. The improved performance of the D* Lite algorithm over other replanning algorithms is largely due to updating terrain cost estimates rather than recalculating them between robot movemen...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006