  Recent researches on robotics have shown significant improvement, spanning
from algorithms, mechanics to hardware architectures. Robotics, including
manipulators, legged robots, drones, and autonomous vehicles, are now widely
applied in diverse scenarios. However, the high computation and data complexity
of robotic algorithms pose great challenges to its applications. On the one
hand, CPU platform is flexible to handle multiple robotic tasks. GPU platform
has higher computational capacities and easy-touse development frameworks, so
they have been widely adopted in several applications. On the other hand,
FPGA-based robotic accelerators are becoming increasingly competitive
alternatives, especially in latency-critical and power-limited scenarios. With
specialized designed hardware logic and algorithm kernels, FPGA-based
accelerators can surpass CPU and GPU in performance and energy efficiency. In
this paper, we give an overview of previous work on FPGA-based robotic
accelerators covering different stages of the robotic system pipeline. An
analysis of software and hardware optimization techniques and main technical
issues is presented, along with some commercial and space applications, to
serve as a guide for future work.
