TY - GEN
T1 - An experimental evaluation of balance strategy based obstacle avoidance
AU - Chang, Ruijuan
AU - Ding, Rong
AU - Lin, Mengxiang
AU - Meng, Dechao
AU - Wu, Zeye
AU - Hang, Meng
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016
Y1 - 2016
N2 - Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate obstacle avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for obstacle avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for obstacle avoidance. Furthermore, some factors contributing to obstacle avoidance ability are studied.
AB - Optical flow plays an important role in vision-based navigation. A lot of optical flow based methods have been developed for autonomous robots. In this paper, we evaluate obstacle avoidance methods based on optical flow in synthetic and real-world scenes. Specifically, the balance strategy is chosen and five representative optical flow algorithms are used. The new metrics for obstacle avoidance performance are introduced. Our experiments demonstrate the effectiveness of the balance strategy for obstacle avoidance. Furthermore, some factors contributing to obstacle avoidance ability are studied.
UR - https://www.scopus.com/pages/publications/85015201503
U2 - 10.1109/ICARCV.2016.7838720
DO - 10.1109/ICARCV.2016.7838720
M3 - 会议稿件
AN - SCOPUS:85015201503
T3 - 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
BT - 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016
Y2 - 13 November 2016 through 15 November 2016
ER -