{'fraction_non_alphanumeric': 0.014629948364888123, 'fraction_numerical': 0.0008605851979345956, 'mean_word_length': 4.933673469387755, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Context Dependent Action Affordances and their Execution using an Ontology of Actions and 3D Geometric Reasoning

When looking at an object humans can quickly and efficiently assess which actions are possible given the scene context. This task remains hard for machines. Here we focus on manipulation actions and in the first part of this study define an object-action linked ontology for such context dependent affordance analysis. We break down every action into three hierarchical pre-condition layers starting on top with abstract object relations (which need to be fulfilled) and in three steps arriving at the movement primitives required to execute the action. This ontology will then, in the second part of this work, be linked to actual scenes. First the system looks at the scene and for any selected object suggests some actions. One will be chosen and, we use now a simple geometrical reasoning scheme by which this action’s movement primitives will be filled with the specific parameter values, which are then executed by the robot. The viability of this approach will be demonstrated by analysing several scenes and a large number of manipulations.