DATE: Wed, Feb 14, 2018
TIME: 1 pm
TITLE: Hybrid Navigation Control for Multi-Behaviour Robots
Fadi Halal
Universite du Quebec a Outaouais

This presentation addresses the issue of designing integrated deliberative-reactive architectures for multi-behaviour robot navigation control. The objective of the study is to devise and investigate a methodology for designing robust planning and control systems equipped with a high level of intelligence and capable of navigating a mobile platform, at a high level of performance, in partly unknown environments, where the mobile robot multi-task operation is subject to different behaviours. Of particular interest in this research are deliberative-reactive navigation systems operating in large, complex environments, such as those applied in environmental monitoring, that make use of a variety of remote sensing data. The spatial data are interpreted intelligently using multi-layer feature maps.

A formal model for hybrid mobile robot navigation is presented. The model integrates two levels of navigation, deliberative and reactive. The novelty in this model is that the decision component makes a decision depending on the global and local context choosing the suitable behaviour, including conflicting behaviours, and regulates the relation between the deliberative and the reactive navigation via computational intelligence techniques. The presented methodology offers a suitable solution for complex partially known environments, where the mobile robot control produces an overall behaviour for executing the proper action in order to reach the target by employing multi-task navigation. In terms of the multi-behaviour operation, the following behaviours are considered: different tasks for environment data acquisition, and different navigation behaviours. In the latter type of behaviours, three situations are studied: dynamic local path, unreachable local path, and conflicting behaviours in a critical situation.

The experiments presented demonstrate the utility of the model in the two fundamental types of the navigation: those with the predominance of the deliberative action, and those with dominant reactive action. The experiments adopted the following methodological approach. First, the deliberative navigation was developed using a hybrid genetic algorithm to deal with multi-task navigation. The proposed navigation system has a flexible and efficient performance along global and local paths. A complete solution for monitoring of water quality in Lake Winnipeg using satellite data was presented. Second, a multi-behaviour deliberative-reactive navigation scheme was designed to deal with conflicting behaviours using artificial intelligence methods, such as fuzzy systems and genetic algorithms, in a hierarchical configuration. The fuzzy control drives the robot to execute the required behaviour, depending on the robot-specific situation and the characteristics of the environment, in order to reach a given target.