Fast CORDIC based Generalized-Voronoi-Diagram Hardware Accelerator for Efficient Robotic Exploration

Zhan，Yi1; Wang，Zihao1; Xu，Jiarui1; Yu，Guoyi1; An，Fengwei2; Chi，Wenzheng3; Wang，Chao1

10.1109/ICRAE50850.2020.9310864

2020-11-20

978-1-7281-8982-6

2020 5th International Conference on Robotics and Automation Engineering, ICRAE 2020

100-105

20-22 Nov. 2020

Singapore, Singapore

This paper proposes a fast-convergence CO-ordinate Rotation DIgital Computer (CORDIC) based Generalized Voronoi Diagram (GVD) hardware accelerator for efficient robotic path exploration. Owing to the high precision contributed by fast-convergence CORDIC, the proposed GVD hardware accelerator significantly improves the accuracy of the explored paths as compared to the baseline design. Higher precision of the exploration causes shorter trajectory of the robot, which further reduces the power consumption of the entire robot system. Therefore, our design is suitable to the battery-powered small-scale robots. FPGA implementation shows that, the proposed design operating at 12-bit fixed point achieves 54% higher precision of the explored paths and 20% lower power consumption of the robot system than the baseline design, respectively.

fast-convergence CORDIC GVD hardware accelerator path exploration

其他

英语

EI

20210609884945

Agricultural robots ; Computational geometry ; Digital computers ; Electric power utilization ; Graphic methods ; Machine design ; Robotics ; Robots

Mechanical Design:601 ; Electric Power Systems:706.1 ; Computer Systems and Equipment:722 ; Digital Computers and Systems:722.4 ; Computer Applications:723.5 ; Robotics:731.5

2-s2.0-85100348531

Scopus

1.Huazhong University of Science and Technology,School of Optical and Electronic Information,Wuhan,China
2.Southern University of Science and Technology,School of Microelectronics,Shenzhen,China
3.Soochow University,School of Mechanical and Electric Engineering,Suzhou,China

Zhan，Yi,Wang，Zihao,Xu，Jiarui,et al. Fast CORDIC based Generalized-Voronoi-Diagram Hardware Accelerator for Efficient Robotic Exploration[C],2020:100-105.