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ALLIANCE: an architecture for fault tolerant multirobot cooperation
1.3K
Citations
27
References
1998
Year
Artificial IntelligenceHeterogeneous Robot TeamHuman-robot Collaborative AssemblyMulti-robot TeamEngineeringAutomationDistributed RoboticsMultirobot SystemRobot Team MembersSystems EngineeringHumanrobot CollaborationComputer ScienceIntelligent SystemsRobot LearningRoboticsMobile RobotsSoftware Architecture
ALLIANCE is a software architecture enabling fault‑tolerant cooperative control of heterogeneous mobile robot teams executing missions of loosely coupled, order‑dependent subtasks. ALLIANCE is a fully distributed, behavior‑based architecture that lets each robot autonomously select actions based on mission requirements, other robots’ activities, environmental conditions, and its own internal states, using mathematically modeled motivations such as impatience and acquiescence to adaptively respond to dynamic environments and team changes. The architecture’s feasibility was demonstrated by implementing it on a mobile robot team that performed a laboratory hazardous waste cleanup.
ALLIANCE is a software architecture that facilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behaviour-based architecture that incorporates the use of mathematically-modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.
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