Papers
1
Total Citations
3
H-Index
1
About
Sen Kong is a researcher in robotics and intelligent control systems, with a primary focus on path planning and autonomous navigation for service robots. Their most cited work, "A Path Planning Algorithm for Sweeping Robot Based on Improved Neural Network" (2019), addresses critical limitations in traditional path planning methods, particularly the lack of self-learning capabilities and poor performance in local path planning. Kong proposed an enhanced neural network-based algorithm that enables sweeping robots to generate collision-free, efficient routes in dynamic environments. This contribution is significant for advancing the autonomy and reliability of domestic cleaning robots, a rapidly growing sector in consumer robotics. Although the paper has garnered 3 citations, it represents an early step in applying neural network techniques to practical robotic navigation challenges. Kong's research bridges the gap between theoretical machine learning models and real-world robotic applications, offering a foundation for future work in adaptive path planning. Their work is particularly relevant for students and researchers interested in the intersection of artificial intelligence, embedded systems, and mobile robotics, highlighting the ongoing need for robust, self-improving navigation solutions in unstructured environments.
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Top Papers
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