Max Robotics — Global Service Robot Directory + US Certification

About

Shiwei Lin is a robotics and autonomous systems researcher whose work spans multi-robot path planning, indoor localization, and bioinspired navigation. With a strong focus on practical applications in warehouse automation and service robotics, Lin has made significant contributions to how mobile robots perceive, navigate, and coordinate within complex real-world environments. Lin's most impactful work includes a comprehensive 2022 review of multi-robot path-planning approaches, which has garnered 145 citations, establishing him as a key synthesizer of knowledge across aerial, ground, and hybrid robotic platforms. Complementing this, his hybrid PSO-SA algorithm for warehouse robot navigation (135 citations) demonstrates his talent for translating theoretical optimization into industry-relevant solutions. His 2023 review of bioinspired perception for service robots further highlights his interest in borrowing principles from nature to advance robotic intelligence. On the localization front, Lin has pioneered sensor fusion techniques combining Ultra-Wideband technology with wheel odometry, addressing the persistent challenge of NLOS errors in indoor environments through both tightly and loosely coupled approaches. His more recent work on distributed online aggregative optimization signals a growing interest in multi-agent coordination under uncertainty. Collectively, Lin's research reflects a researcher steadily building toward fully autonomous, adaptive robotic systems for real-world deployment.