Neuro-Symbolic Manipulation Understanding with Enriched Semantic Event Chains
Robotic systems operating in human environments must reason about how object interactions evolve over time, which actions are currently being performed, and what manipulation step is likely to follow. Classical enriched Semantic Event Chains (eSECs) provide an interpretable relational description of manipulation, but remain primarily descriptive and do not directly support uncertainty-aware decision making. In this paper, we propose eSEC-LAM, a neuro-symbolic framework that transforms eSECs into an explicit event-level symbolic state for manipulation understanding. The proposed formulation augments classical eSECs with confidence-aware predicates, functional object roles, affordance prior...
| Authors | Fatemeh Ziaeetabar |
|---|---|
| Primary category | cs.RO |
| Published | 22 April 2026 |
| Last updated at source | 22 April 2026 |
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