Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Introduction to AI Robotics
An Behavior-based Robotics
Exploring artificial intelligence in the new millennium
Introduction to Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots
Journal of Robotic Systems - Special Issue on the DARPA Grand Challenge, Part 2
A convergent dynamic window approach to obstacle avoidance
IEEE Transactions on Robotics
Map-based navigation in mobile robots
Cognitive Systems Research
Development of a reduced human user input task allocation method for multiple robots
Robotics and Autonomous Systems
Towards a robust feedback system for coordinating a hierarchical multi-robot system
Robotics and Autonomous Systems
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Navigation systems often play an important role in mobile robot control. Many existing mobile robot navigation systems have been implemented and tested for particular types of robots. However, in some implementations, such as heterogeneous multi-robot systems, a generic navigation system can offer potential advantages. In such applications, a generic navigation system should be able account for robots with varying size, shape, drive type and sensor quantities. Additionally, it should be capable of offering a high degree of flexibility for navigation in known and unknown environments. Hence, a single generic navigation system that combines the benefits of reactive and deliberative control has been developed for heterogeneous mobile robots. The design of the hierarchical hybrid navigation system is based on the A* algorithm, a polar histogram and a modified dynamic window approach. Simulation experiments with three heterogeneous robots in a range of environments have been conducted. Performance of reactive navigation and hybrid reactive-deliberative navigation in known and unknown environments is evaluated. Favourable results are achieved with the developed reactive system. Hybrid reactive-deliberative navigation offers improved performance over reactive navigation in known environments. Deliberative control does not affect performance significantly in unknown environments. Initial hardware experiments demonstrate that the navigation system can work on real robots.