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Execution Monitoring for Long-Term Autonomous Plant Observation with a Mobile Robot

Long-term autonomous robotic systems in highly dynamic real-world applications are becoming a reality. Nonetheless, ensuring a certain level of robustness for these systems is a major challenge, as it is impossible to anticipate all potential situations that a robot might encounter. A joint consistent integration of both monitoring and acting is vital, as plans do not always work out as expected when faced with the chaotic nature of reality. Consequently, execution monitoring techniques that address unexpected problematic situations by means of recovery mechanisms must be an essential component of robot architectures. This thesis attempts to reduce the barriers towards long-term autonomy of mobile outdoor robots by identifying and classifying key difficulties in such a context and developing a fully integrated monitoring and resolution framework capable of overcoming some of the typical limitations for those systems. Experimental evaluation of the proposed framework in a simulation environment indicates a drastically improved resilience with respect to the identified challenges.

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Master's Thesis at Osnabrueck University / DFKI

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