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About

Pengkun Zhou is a robotics researcher whose work lies at the intersection of real-time perception, localization, and autonomous navigation in dynamic environments. His most significant contribution is PointSLOT (2023, 23 citations), a pioneering framework that simultaneously performs SLAM and object tracking in real time, directly addressing the critical limitation of scene rigidity that constrains traditional SLAM algorithms—a breakthrough essential for applications like autonomous driving and multi-robot collaboration. Zhou also advanced hardware-accelerated robotics with his work on a resource-efficient Harris corner detection accelerator for Visual Inertial Odometry on FPGA platforms (2022, 9 citations), demonstrating expertise in bridging algorithmic efficiency with embedded systems. Earlier in his career, he explored human-robot interaction through the design and control of a back massage robot (2019, 5 citations), showcasing versatility in mechatronic design. His most recent work, VF-Nav (2025), extends navigation research into visual floor-plan-based point-goal navigation. With a trajectory spanning from hardware acceleration to dynamic SLAM, Zhou is establishing himself as a researcher who tackles fundamental challenges in making robots perceive and operate reliably in the real world.