Papers
6
Total Citations
27
H-Index
3
About
Grimaldo Silva is a leading researcher in human-robot interaction (HRI), with a focus on developing intuitive, safe, and collaborative robotic systems. His work centers on three key areas: human-robot motion planning, collision avoidance, and multimodal interaction for industrial assembly. Silva’s major contributions include pioneering a "shared effort" approach to human-robot motion, where both agents dynamically distribute responsibility during navigation, as detailed in his most-cited paper (2017, 9 citations). He has also advanced predictive intention recognition using deep learning (2024, 3 citations) and introduced an augmented video interface supported by deep learning for multi-perspective HRI (2022, 6 citations). His research on effective collaboration in near-symmetry collision scenarios (2019, 3 citations) and human-inspired effort distribution during collision avoidance (2018, 4 citations) has deepened understanding of cooperative motion. Most recently, Silva has explored LLM-enhanced multimodal interaction for assembly tasks (2025, 2 citations), aligning with the growing Robot as a Service (RaaS) model. With a cumulative impact of over 27 citations, Silva’s work is shaping the future of seamless, adaptive human-robot collaboration in both research and industrial settings.
Research Focus
Key Achievements
Top Papers
- 1Human robot motion: A shared effort approach9 citations · 2017
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- 5Effective Human-Robot Collaboration in near symmetry collision scenarios3 citations · 2019
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