TY - GEN
T1 - GPU-based heuristic escape for outdoor large scale registration
AU - Yin, Peng
AU - Gu, Feng
AU - Li, Decai
AU - He, Yuqing
AU - Yang, Liying
AU - Han, Jianda
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2016/12/14
Y1 - 2016/12/14
N2 - Heterogeneous robot introduce a higher perception ability than single type robots in outdoor environments. One key problem is to making the 3D environmental model from the cooperated robots in real time, especially in the unstructured environment. Based on our previous work on outdoor environment registration method, in this paper, we introduce a GPU based Enhanced ICP method for large-scale heterogeneous robot registration. First, we combine the GPU-based nearest neighbor search in the traditional ICP framework. Second, we proposed a measurement and estimation model for the local minima problem. Third, we proposed a GPU-based heuristic escape method to generate the escaping transformation in real time. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the performance of the proposed method. © 2016 IEEE.
AB - Heterogeneous robot introduce a higher perception ability than single type robots in outdoor environments. One key problem is to making the 3D environmental model from the cooperated robots in real time, especially in the unstructured environment. Based on our previous work on outdoor environment registration method, in this paper, we introduce a GPU based Enhanced ICP method for large-scale heterogeneous robot registration. First, we combine the GPU-based nearest neighbor search in the traditional ICP framework. Second, we proposed a measurement and estimation model for the local minima problem. Third, we proposed a GPU-based heuristic escape method to generate the escaping transformation in real time. Experiments involving one unmanned aerial vehicle and one unmanned surface vehicle were conducted to verify the proposed technique. The experimental results were compared with those of normal ICP registration algorithms to demonstrate the performance of the proposed method. © 2016 IEEE.
UR - https://www.scopus.com/pages/publications/85010028179
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85010028179&origin=recordpage
U2 - 10.1109/RCAR.2016.7784036
DO - 10.1109/RCAR.2016.7784036
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467389594
T3 - 2016 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2016
SP - 260
EP - 265
BT - 2016 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2016
PB - IEEE
T2 - 2016 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2016
Y2 - 6 June 2016 through 9 June 2016
ER -