Planning for conjunctive goals
Artificial Intelligence
The Navlab system for mobile robot navigation
The Navlab system for mobile robot navigation
Reliable goal-directed reactive control of autonomous mobile robots
Reliable goal-directed reactive control of autonomous mobile robots
A Colony Architecture for an Artificial Creature
A Colony Architecture for an Artificial Creature
A Distributed Model for Mobile Robot Environment-Learning and Navigation
A Distributed Model for Mobile Robot Environment-Learning and Navigation
Adaptive execution in complex dynamic worlds
Adaptive execution in complex dynamic worlds
An architectural approach to ensuring consistency in hierarchical execution
Journal of Artificial Intelligence Research
Finding and exploiting goal opportunities in real-time during plan execution
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A learning approach to integration of layers of a hybrid control architecture
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Robotics software frameworks for multi-agent robotic systems development
Robotics and Autonomous Systems
Cognitive architectures: Research issues and challenges
Cognitive Systems Research
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We present an architecture for controlling autonomous mobile robots based on control of continuous activities (processes) rather than discrete actions. We define a hierarchy of activity, and argue that different levels of activities require different sorts of computational mechanisms to control them. Many controversial issues concerning the use of persistent internal state and higher levels of abstraction can be better understood in terms of this hierarchy. Two experiments using the architecture to control mobile robots performing complex navigation tasks are described.