Natural language, a primary communication medium for humans, facilitates better human-machine interaction and could be an efficient means to use intelligent robots in a more flexible manner. In this paper, we report on our joint efforts at providing natural language access to the autonomous mobile two-arm robot Kamro. The robot is able to perform complex assembly tasks. To achieve autonomous behaviour, several camera systems are used for the perception of the environment during task execution. Since natural language utterances must be interpreted with respect to the robot's current environment the processing must be based on a referential semantics that is perceptually anchored. Considering localization expressions, we demonstrate how, on the one hand, verbal descriptions, and on the other hand, knowledge about the physical environment, i.e., visual and geometric information, can be connected to each other.

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The paper summarizes different types of interaction (communication, cooperation and coordination) in multi-robot-systems. Robot interaction can be part of perception, planning, and execution. It is possible to distinguish physical interactions between robots and environment and interactions for joint information processing between the robots. Physical interactions can be intended or can be an unexpected side effect. For controlling physical interactions either local information processing strategies (compensation, etc.) or joint information processing strategies (resource management, closed kinematic control, etc.) can be used. The strategies described here have been developed and implemented for the Karlsruhe Autonomous Cooperative Robot Systems. They are based on distributed planning, dynamically changing control architectures and local communication.

Most of the existing autonomous robot systems have a centralized hierarchical control architecture. In such robot systems, all planning, execution control, and monitoring tasks are performed by a single control unit on a defined level. In case of an error that occurs during the execution, this central control unit has the complete knowledge about the past executed actions and is able to reason on the error situation. Besides the centralized control architectures, distributed and decentralized control architectures have been developed to overcome some problems with the centralized systems. Because of the missing overall control, error recovery is more difficult than in centralized systems. This paper presents concepts to obtain fault-tolerance behaviour and error recovery in a distributed controlled robot system. As an example for such a robot system, the Karlsruhe Autonomous Mobile Robot KAMRO is considered that is being developed at IPR. Many experiments were performed with the former centralized control architecture. Our intention is to achieve the same and better results with the distributed control architecture KAMARA.