Abstract
As the Fourth Industrial Revolution reshapes industrial paradigms, human-robot collaboration (HRC) has transitioned from a desirable capability to an operational necessity. In response, collaborative robots are evolving beyond repetitive tasks toward adaptive, semantically informed interaction with humans and environments. This paper surveys five foundational pillars enabling this transformation: semantic-level perception, cognitive action planning, explainable learning and control, safety-aware motion design, and multimodal human-intention recognition. We examine the role of semantic mapping in transforming spatial data into meaningful context, and explore cognitive planning frameworks that leverage this context for goal-driven decision-making. We analyze explainable reinforcement-learning methods — including policy distillation and attention mechanisms — which enhance interpretability and trust. Safety is addressed through force-adaptive control and risk-aware trajectory planning; seamless human interaction is supported via gaze- and gesture-based intent recognition. To address the remaining challenges, we propose a unified Cognitive Synergy Architecture integrating all modules into a cohesive framework for truly human-centric cobot collaboration.
A review article surveying the five pillars of cognitive
collaborative robotics and proposing a unified Cognitive Synergy
Architecture as a roadmap. The review is explicitly a preprint — not
yet peer-reviewed at the time of this listing.
- Semantic-level perception — transforming geometric maps into
meaningful context.
- Cognitive action planning — goal-driven decision-making that
leverages semantic context.
- Explainable learning and control — policy distillation,
attention mechanisms, interpretable reinforcement learning.
- Safety-aware motion design — force-adaptive control and
risk-aware trajectory planning.
- Multimodal human-intention recognition — gaze, gesture, and
language channels fused into a single intent estimate.
Conceptual precursor to the SEGO architecture
paper, which instantiates parts of
the proposed architecture in code.