Makoto Kadowaki
Papers
1
Total Citations
6
H-Index
1
About
Makoto Kadowaki is a researcher whose work lies at the intersection of robotics, sensor-based motion planning, and automated assembly. His most cited contribution, "A near-optimal sensor-based motion-planning algorithm for parts mating" (2002), addresses a fundamental challenge in industrial robotics: how to guide a robot to mate parts when the environment is partially unknown. Kadowaki’s key insight was to exploit the unique geometry of parts mating tasks, where only a single unknown obstacle exists in configuration space. This allowed him to design an algorithm that efficiently seeks a deadlock-free path to a target point, achieving near-optimal performance with minimal sensor feedback. Though his citation count is modest (6 citations), the work is notable for its theoretical elegance and practical relevance to automated manufacturing. Kadowaki’s research bridges the gap between theoretical motion planning and real-world robotic assembly, offering a principled approach to a problem that remains central to modern robotics. His algorithm stands as a clear, solution-oriented contribution to sensor-based planning, demonstrating how domain-specific constraints can be leveraged for computational efficiency.
Research Focus
Key Achievements
Top Papers
- 1A near-optimal sensor-based motion-planning algorithm for parts mating6 citations · 2002