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Robotic computing system and embodied AI evolution: an algorithm-hardware co-design perspective

Authors: YAN Longke; ZHAO Xin; YANG Bohan; WU Yongkun; DAI Guangnan; LI Jiancong; TSUI Chi-Ying; CHENG Kwang-Ting; ZHANG Yihan; TU Fengbin

DOI: 10.1088/1674-4926/25020034Status: Verified Translated Edition
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Key Findings in This Report

• Robotic algorithms are evolving from traditional to hierarchical and end-to-end models, posing challenges for balanced system-wide performance. • Algorithm-hardware co-design is essential to analyze computational properties and drive both algorithm optimization and hardware innovation. • Recent works demonstrate co-design across robotic and embodied AI algorithms and computing hardware, achieving high performance and energy efficiency. • Future research must adapt computing platforms to rapid embodied AI evolution and leverage emerging hardware for end-to-end inference improvements.