Papers
3
Total Citations
42
H-Index
3
About
Yiyi Cai is a leading researcher in autonomous mobile robotics, specializing in sensor fusion, simultaneous localization and mapping (SLAM), and deep reinforcement learning for path planning. Their work addresses critical challenges in enabling robots to navigate unknown and dynamic environments without relying on predefined maps. Cai’s most-cited paper, “Autonomous Navigation by Mobile Robot with Sensor Fusion Based on Deep Reinforcement Learning” (2024, 27 citations), pioneers the integration of deep reinforcement learning with multisensor data to overcome the limitations of conventional path-planning algorithms. They further advanced the field with a novel SLAM scheme using RBPF-SLAM and multisensor fusion (2022, 8 citations), solving problems of particle depletion and long runtimes. Their 2024 paper on the Adaptive Deep Ant Colony Optimization–Asymmetric Strategy Network Twin Delayed Deep Deterministic Policy Gradient algorithm (7 citations) introduces a hybrid approach that dramatically improves convergence speed and avoids local optima in complex dynamic environments. Cai’s work consistently bridges theoretical innovation with practical deployment, making significant contributions to intelligent robotics and autonomous systems.
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