A new approach for context based exception handling in autonomous mobile service robots

Free navigating robots are applied to increasingly complex tasks in both the industrial and service sectors. With task complexity rising, the likelihood of unexpected events is increasing. Advanced service robots therefore require intelligent controllers to handle task oriented exceptions, to select appropriate countermeasures and to execute these efficiently. In order to manage and to perform appropriately and to handle cascaded exceptions as well, systematic knowledge gathering, analysis and representation is required Here relational data models are extensively used to generate measures in case of external or internal exceptions, and to accept and store new information for use in similar situations. A hierarchical controller architecture that has been developed and verified using Petri net models, supervises planned task execution and enforces the measures required for successful autonomous operation. The efficiency of the proposed exception handling approach has been tested and evaluated with the mobile robot MACROBE performing several inspection and transportation tasks in a shop floor environment