Incremental Search

Incremental search algorithms reuse information from previous searches to speed up the current search and solve search problems potentially much faster than solving them repeatedly from scratch. They are widely popular in solving dynamic path-planning problems such as navigation for unmanned ground vehicles and motion planning for articulated robots. For example, existing incremental search algorithms such as D* and D* Lite have been adapted for use with much success in various robotic applications including the Mars rovers and autonomous vehicles in the DARPA Urban Challenge.

Our current research focus is on investigating the applicability of such algorithms in conjunction with answer set programming to solve multi-agent pathfinding problems. Applications of this problem is numerous including the coordination of robots in automated warehouses.

Group Members and Current Collaborators
  • Van Nguyen, New Mexico State University
  • Philipp Obermeier, University of Potsdam
  • Torsten Schaub, University of Potsdam
  • Tran Cao Son, New Mexico State University
Recent Publications