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Improving Robustness of Task Execution Against External Faults Using Simulation Based Approach
(2013)
Robots interacting in complex and cluttered environments may face unexpected situations referred to as external faults which prohibit the successful completion of their tasks. In order to function in a more robust manner, robots need to recognise these faults and learn how to deal with them in the future. We present a simulation-based technique to avoid external faults occurring during execusion releasing actions of a robot. Our technique utilizes simulation to generate a set of labeled examples which are used by a histogram algorithm to compute a safe region. A safe region consists of a set of releasing states of an object that correspond to successful performances of the action. This technique also suggests a general solution to avoid the occurrence of external faults for not only the current, observable object but also for any other object of the same shape but different size.
Unexpected Situations in Service Robot Environment: Classification and Reasoning Using Naive Physics
(2014)
In the realm of service robots recovery from faults is indispensable to foster user acceptance. Here fault is to be understood not in the sense of robot internal, rather as interaction faults while situated in and interacting with an environment (aka ex-ternal faults). We reason along the most frequent failures in typical scenarios which we observed during real-world demonstrations and competitions using our Care-O-bot III 1 robot. They take place in an apartment-like environments which is known as closed world. We suggest four different -for now adhoc -fault categories caused by disturbances, imperfect per-ception, inadequate planning or chaining of action sequences. The fault are categorized and then mapped to a handful of partly known, partly extended fault handling techniques. Among them we applied qualitative reasoning, use of simu-lation as oracle, learning for planning (aka en-hancement of plan operators) or -in future -case-based reasoning. Having laid out this frame we mainly ask open questions related to the applicability of the pre-sented approach. Amongst them: how to find new categories, how to extend them, how to as-sure disjointness, how to identify old and label new faults on the fly.
The work presented in this paper focuses on the comparison of well-known and new techniques for designing robust fault diagnosis schemes in the robot domain. The main challenge for fault diagnosis is to allow the robot to effectively cope not only with internal hardware and software faults but with external disturbances and errors from dynamic and complex environments as well.