Grammatical Robotics: A pāṇinian vyākaraṇa framework for task specification and human robot interaction

The paper presents a novel interdisciplinary framework integrating principles from Pāṇinian Sanskrit Vyākaraṇa (grammar) with modern robotic task specification, motion planning, and human‑robot interaction. Sanskrit grammar, particularly as formulated by Pāṇini in the Aṣṭādhyāyī, offers a highly structured, rule‑based, and generative system for constructing meaningful utterances from atomic components. The author argue that this linguistic architecture provides a powerful meta‑model for designing robotic systems capable of generating complex, context‑appropriate behaviour from a finite set of primitives and rules. The core of our approach lies in mapping key Vyākaraṇa concepts such as dhātu (verbal root), kāraka (thematic roles), sūtra (generative rule), and samāsa (composition) onto computational structures in robotics. The author demonstrate how a kāraka-based formalism can parse natural language commands into role‑based task representations, enabling robots to infer intent and relationships between actions, agents, objects, and instruments. Furthermore, the author show how Pāṇini’s context‑sensitive, generative rule system can be adapted to create hierarchical task grammars for flexible action sequencing. The author present experimental validation in two domains: a simulated kitchen‑assistant robot performing multi‑step manipulation tasks, and a natural‑language‑guided mobile robot. Results indicate that the Vyākaraṇa‑inspired framework improves task interpretability, supports the generation of novel, unprogrammed action sequences, and enhances the robustness of instruction parsing compared to standard keyword‑or template‑based methods. This work establishes a foundation for “grammatical robotics” a paradigm where embodied agents reason and act according to formal, generative, and semantically grounded principles derived from linguistic science.