Affordance-based task communication methods for astronaut-robot cooperation

摘要

The problem with current human-robot task communication is that robots cannot understand complex human speech utterances, while humans cannot efficiently use the fixed task request utterances required by robots. Nonetheless, future planetary exploration missions are expected to require astronauts on extra-vehicular activities to communicate task requests to robot assistants with speech- and gesture-type user interfaces that can be easily embedded in their space suits. The solution proposed in this thesis is indirect task communication based on the human-like ability to utilise object-action relationships in task communication. Conventional task communication methods, in which all task parameters need to be communicated explicitly, are evaluated against task communication methods where affordances, i.e. action possibilities, are used to complete task communication. These so-called affordance-based task communication methods are evaluated by means of four user experiments: two performed with a fully autonomous centauroid robot in a planetary exploration work context and two with a simulated robot in a lander assembly work context. The first two experiments are performed in unambiguous work environments, where each object is associated with only one action and vice versa, while the last two experiments are performed in ambiguous work environments, where each object and action is normally associated with several actions and objects, respectively. The user experiments show that affordance-based task communication methods can be used to decrease both the human workload and task communication times in a planetary exploration work context. Furthermore, affordance-based task communication methods are found to be preferred over conventional task communication methods. The affordance-based task communication methods derived can be applied to facilitate any human-robot task communication that includes a priori known or recurring task sequences. In this thesis, the feasibility of the approach was demonstrated for frame-based dialogue managers, which are widely used in robotics.