1 |
A. Krause, A. Singh, and C. Guestrin, "Nearoptimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical studies," Journal of Machine Learning Research, Vol.9, pp.235-284, Feb. 2008.
|
2 |
H. Durrant-Whyte, F. Ramos, E. Nettleton, A. Blair, and S. Vasudevan, "Gaussian process modeling of large scale terrain," in Proc. of the 2009 IEEE International Conference on Robotics and Automation, 2009.
|
3 |
S. Petti and T. Fraichard, "Safe motion planning in dynamic environments," in IEEE-RSJ Int. Conf. on Intelligent Robots and Systems, Aug. 2005.
|
4 |
C. M. Bishop, "Pattern Recognition and Machine Learning," Springer, New York, 2006
|
5 |
J. V. der Berg, P. Abbeel, and K. Goldberg, "LPG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information," The International Journal of Robotics Research, Vol.30, pp.895-913, Jun. 2011.
DOI
|
6 |
C. Fulgenzi, C. Tay, A. Spalanzani, and C. Laugier, "Probabilistic navigation in dynamic environment using rapidly-exploring random trees and gaussian processes," in Intelligent Robots and Systems, Nice, Sep. 2008, pp.1056-1062.
|
7 |
M. Zucker, J. Kuffner, and M. Branicky, "Multipartite rrts for rapid replanning in dynamic environments," in IEEE International Conference on Robotics and Automation, Apr. 2007.
|
8 |
Y. Kuwata, G. A. Fiore, J. Teo, E. Frazzoli, and J. P. How, "Motion planning for urban driving using rrt," in IEEE/RSJ Intl. Conference on Intelligent Robotics and Systems, Sep. 2008.
|
9 |
C. Urmson and R. Simmons, "Approaches for heuristically biasing rrt growth," in IEEE/RSJ Intl. Conference on Intelligent Robotics and Systems, Oct. 2003.
|
10 |
D. Ferguson and A. Stentz, "Cost based planning with rrt in outdoor environment," in IEEE/RSJ Intl. Conference on Intelligent Robotics and Systems, Oct. 2006.
|
11 |
M. N. Gibbs and D. J. C. MacKay, "Efficient implementation of gaussian processes," Cambridge, Tech. Rep. 1997.
|
12 |
J. Choi, J. Lee, and S. Oh, "Swarm intelligence for achieving the global maximum using spatio-temporal gaussian processes," in American Control Conference, Seattle, WA, Jun. 2008, pp.135-140.
|
13 |
C. E. Rasmussen and C. K. Williams, Eds., Gaussian Processes for Machine Learning. Cambridge: The MIT Press, 2006.
|
14 |
N. Cressie, "Kriging nonstationary data," Journal of the American Statistical Association, Vol.81, pp.625-634, Nov. 1986.
DOI
|
15 |
B. Ferris, D. Fox, and N. Lawrence, "WiFi-SLAM using Gaussian process latent variable models," in Proc. of the 20th International Joint Conference on Artificial Intelligence, 2007.
|
16 |
D. Kim and D. Kang, "Optimal Path Planning of Mobile Robot for Multiple Moving Obstacles," The Journal of Korea Robotics Society, Vol.2, pp.183-190, 2007.
|
17 |
S. Rodriguez, X. Tang, J. Lien, and N. M. Amato, "An obstacle-based rapidly-exploring random tree," in IEEE International Conference on Robotics and Automation, May 2006.
|
18 |
J. Beak and C. Lee, "An Analysis on the Influential Factors to Set the Path Planning Algorithm for Unmanned Ground Vehicle in Combat Environment," The Journal of Korea Robotics Society, Vol.4, pp.233-242, Aug. 2009.
|
19 |
Y. Chang and Y. Yamamoto, "Path planning of wheeled mobile robot with simultaneous free space locating capability," Intelligent Service Robotics, Vol.2, pp.9-22, 2009.
DOI
|
20 |
S. M. LaValle and J. J. Kuffner, "Randomized kinodynamic planning," The International Journal of Robotics Research, Vol.20, pp.378-400, May 2001.
DOI
|
21 |
N. A. Melchior and R. Simmons, "Particle RRT for path planning with uncertainty," in IEEE International Conference on Robotics and Automation, Roma, Apr. 2007.
|