Jutao Wang

Tianjin University of Technology, Tianjin University of Technology and Education

Papers

Total Citations

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About

Jutao Wang is a robotics researcher whose work bridges the gap between autonomous navigation and dexterous manipulation. His primary research areas include robot path planning, intelligent optimization algorithms, and soft-rigid hybrid gripper design. Wang’s most impactful contribution is his 2018 paper on “Robot Path Planning Based on Improved Ant Colony Algorithm,” which has accumulated 36 citations—the highest among his works. In this study, he addressed critical limitations of the basic ant colony algorithm, such as slow convergence, low efficiency, and susceptibility to local optima, by introducing an artificial potential field to enhance search performance. He further advanced path planning for industrial applications with his 2019 work on sandblasting robots, proposing an improved Rapidly-exploring Random Tree (RRT) algorithm tailored for traversing complex workpiece geometries. Most recently, in 2025, Wang published a novel design for a soft-rigid hybrid gripper that mimics biological ligaments and joint capsules, achieving a balance between static stability and flexible compliance for unstructured grasping tasks. His trajectory from algorithmic optimization to bio-inspired hardware design demonstrates a commitment to solving real-world robotic challenges, making his work relevant for students and researchers in autonomous systems and soft robotics.