RoboCup 2007: Robot Soccer World Cup XI
Agent-Based Approach to Free-Flight Planning, Control, and Simulation
IEEE Intelligent Systems
Agents towards vehicle routing problems
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A multi-agent system for obtaining dynamic origin/destination matrices on intelligent road networks
Proceedings of the 6th Euro American Conference on Telematics and Information Systems
| Hi-index | 0.00 |
Navigation of unmanned ground vehicles in an urban area is a fundamental problem which has to be solved prior to real-world deployment of the autonomous ground assets. Since the topology data of the environment are usually known a priori, they can be exploited in high-level planning of the routes. On the other hand, the low-level robot control requires precise path to follow and thus trajectory planning has to be adopted as well. Finally, the particular details of the environment can differ from the known topology and thus the vehicles need an area exploration method. The integrated multi-agent system for cooperative navigation in partially unknown urban environment is introduced and validated using vehicle physics based simulation. The goal is to support the navigation of a convoy by a set of unmanned vehicles in an urban environment to avoid convoy stops or u-turns and minimize the total traveled distance of all vehicles. The high-level planning component (long-time horizon) is based on distributed problem solver (DPS) together with a D-star route planner, where the DPS solves a dynamic vehicle routing problem over a set of generated frontiers describing interesting points in the map. After allocation of the tasks, each vehicle uses an adaptive path planner (short-time horizon) for generation of the precise path, which is then followed. Any new information sensed by the vehicles is additionally integrated into the global knowledge and can influence the planning processes.