Sijia Tian

Huazhong University of Science and Technology

Papers

Total Citations

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About

Sijia Tian’s research lies at the intersection of robotics, real-time motion planning, and hardware acceleration, with a focus on improving the efficiency and safety of autonomous robotic systems. Her major contributions include pioneering the use of FPGA-based design to accelerate collision detection for real-time robot motion planning—a critical challenge in dynamic environments where computational speed is paramount. Her 2019 paper on this topic, cited 6 times, demonstrates a novel hardware-software co-design approach that significantly reduces latency in robotic arm applications. In her 2020 work on optimal path planning for a robot shelf-picking system, she tackled the practical problem of generating the shortest picking sequence for a 6-degree-of-freedom robot, directly enhancing warehouse automation efficiency. Though early in her career, Tian’s work has already garnered attention for its practical impact on industrial robotics, bridging the gap between theoretical motion planning algorithms and real-time, hardware-accelerated implementations. Her research is particularly relevant for students and engineers interested in embedded systems, FPGA design, and the future of autonomous logistics.