Fetching the paper…
Reading the bibliography…
Constrained motion planning is a challenging field of research, aiming for computationally efficient methods that can find a collision-free path on the constraint manifolds between a given start and goal configuration.
M. P. Lawton and E. M. Brody, “Assessment of older people: self-maintaining and instrumental activities of daily living,” The gerontologist , vol. 9, no. 3_Part_1, pp. 179–186, 1969
1969
Earlier work this paper cites.
Y. Koga, K. Kondo, J. Kuffner, and J.-C. Latombe, “Planning motions with intentions,” in Proceedings of the 21st annual conference on Computer graphics and interactive techniques , 1994, pp. 395–408
1994
Earlier work this paper cites.
L. E. Kavraki and J.-C. Latombe, “Probabilistic roadmaps for robot path planning,” Pratical motion planning in robotics: current approaches and future challenges , pp. 33–53, 1998
1998
Earlier work this paper cites.
S. M. LaValle, “Rapidly-exploring random trees: A new tool for path planning,” 1998. [Online]. Available: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.35.1853
1998
Earlier work this paper cites.
M. Spivak, “A comprehensive introduction to differential geometry,” A Comprehensive Introduction to Differential Geometry. Publish or Perish , no. 3, 1999
1999
Earlier work this paper cites.
L.-W. Tsai, Robot analysis: the mechanics of serial and parallel manipulators . John Wiley & Sons, 1999
1999
Earlier work this paper cites.
R. Cooper and T. Shallice, “Contention scheduling and the control of routine activities,” Cognitive neuropsychology , vol. 17, no. 4, pp. 297–338, 2000
2000
Earlier work this paper cites.
J. J. Kuffner Jr and S. M. LaValle, “Rrt-connect: An efficient approach to single-query path planning,” in ICRA , vol. 2, 2000
2000
Earlier work this paper cites.
L. Han, “A kinematics-based probabilistic roadmap method for closed chain systems,” in In Proc. Int. Workshop on Algorithmic Foundations of Robotics (WAFR , 2000
2000
Earlier work this paper cites.
J. H. Yakey, S. M. LaValle, and L. E. Kavraki, “Randomized path planning for linkages with closed kinematic chains,” IEEE Transactions on Robotics and Automation , vol. 17, no. 6, pp. 951–958, 2001
2001
Earlier work this paper cites.
M. E. Henderson, “Multiple parameter continuation: Computing implicitly defined k-manifolds,” International Journal of Bifurcation and Chaos , vol. 12, no. 03, pp. 451–476, 2002
2002
Earlier work this paper cites.
G. H. Ballantyne and F. Moll, “The da vinci telerobotic surgical system: the virtual operative field and telepresence surgery,” Surgical Clinics , vol. 83, no. 6, pp. 1293–1304, 2003
2003
Earlier work this paper cites.
K. Yamane, J. J. Kuffner, and J. K. Hodgins, “Synthesizing animations of human manipulation tasks,” in ACM SIGGRAPH , 2004, pp. 532–539
2004
Earlier work this paper cites.
H. M. Choset, S. Hutchinson, K. M. Lynch, G. Kantor, W. Burgard, L. E. Kavraki, and S. Thrun, Principles of robot motion: theory, algorithms, and implementation . MIT press, 2005
2005
Earlier work this paper cites.
Z. Yao and K. Gupta, “Path planning with general end-effector constraints: Using task space to guide configuration space search,” in 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2005, pp. 1875–1880
2005
Earlier work this paper cites.
S. M. LaValle, Planning algorithms . Cambridge university press, 2006
2006
Earlier work this paper cites.
R. Pfeifer and J. Bongard, How the body shapes the way we think: a new view of intelligence . MIT press, 2006
2006
Earlier work this paper cites.
D. W. Schneider and G. D. Logan, “Hierarchical control of cognitive processes: switching tasks in sequences.” Journal of Experimental Psychology: General , vol. 135, no. 4, p. 623, 2006
2006
Earlier work this paper cites.
C. Ott, O. Eiberger, W. Friedl, B. Bauml, U. Hillenbrand, C. Borst, A. Albu-Schaffer, B. Brunner, H. Hirschmuller, S. Kielhofer et al. , “A humanoid two-arm system for dexterous manipulation,” in 2006 6th IEEE-RAS International Conference on Humanoid Robots . IEEE, 2006, pp. 276–283
2006
Earlier work this paper cites.
J. M. Zacks, N. K. Speer, K. M. Swallow, T. S. Braver, and J. R. Reynolds, “Event perception: a mind-brain perspective.” Psychological bulletin , vol. 133, no. 2, p. 273, 2007
2007
Earlier work this paper cites.
M. Stilman, “Task constrained motion planning in robot joint space,” in 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2007, pp. 3074–3081
2007
Earlier work this paper cites.
M. V. Weghe, D. Ferguson, and S. S. Srinivasa, “Randomized path planning for redundant manipulators without inverse kinematics,” in 2007 7th IEEE-RAS International Conference on Humanoid Robots . IEEE, 2007, pp. 477–482
2007
Cited alongside, same era.
N. Ratliff, M. Zucker, J. A. Bagnell, and S. Srinivasa, “Chomp: Gradient optimization techniques for efficient motion planning,” in 2009 IEEE International Conference on Robotics and Automation . IEEE, 2009, pp. 489–494
2009
Cited alongside, same era.
M. Stilman, “Global manipulation planning in robot joint space with task constraints,” IEEE Transactions on Robotics , vol. 26, no. 3, pp. 576–584, 2010
2010
Cited alongside, same era.
S. Karaman and E. Frazzoli, “Sampling-based algorithms for optimal motion planning,” The international journal of robotics research , vol. 30, no. 7, pp. 846–894, 2011
2011
Cited alongside, same era.
L. Jaillet and J. M. Porta, “Path planning with loop closure constraints using an atlas-based rrt,” in Robotics Research . Springer, 2017, pp. 345–362
2017
Later among the works it cites.
A. Conneau, D. Kiela, H. Schwenk, L. Barrault, and A. Bordes, “Supervised learning of universal sentence representations from natural language inference data,” in Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing . Copenhagen, Denmark: Association for Computational Linguistics, September 2017, pp. 670–680
2017
Later among the works it cites.
L. Trottier, P. Gigu, B. Chaib-draa et al. , “Parametric exponential linear unit for deep convolutional neural networks,” in 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA) . IEEE, 2017, pp. 207–214
2017
Later among the works it cites.
Z. Tahir, A. H. Qureshi, Y. Ayaz, and R. Nawaz, “Potentially guided bidirectionalized rrt* for fast optimal path planning in cluttered environments,” Robotics and Autonomous Systems , vol. 108, pp. 13–27, 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
D. Berenson, S. Srinivasa, and J. Kuffner, “Task space regions: A framework for pose-constrained manipulation planning,” The International Journal of Robotics Research , vol. 30, no. 12, pp. 1435–1460, 2011
2011
Cited alongside, same era.
J. Duchi, E. Hazan, and Y. Singer, “Adaptive subgradient methods for online learning and stochastic optimization.” Journal of machine learning research , vol. 12, no. 7, 2011
2011
Cited alongside, same era.
I. A. Şucan, M. Moll, and L. E. Kavraki, “The Open Motion Planning Library,” IEEE Robotics & Automation Magazine , vol. 19, no. 4, pp. 72–82, December 2012, https://ompl.kavrakilab.org
2012
Cited alongside, same era.
L. Jaillet and J. M. Porta, “Efficient asymptotically-optimal path planning on manifolds,” Robotics and Autonomous Systems , vol. 61, no. 8, pp. 797–807, 2013
2013
Cited alongside, same era.
L. Jaillet and J. M. Porta, “Asymptotically-optimal path planning on manifolds,” Robotics: Science and Systems VIII , pp. 145–152, 2013
2013
Cited alongside, same era.
J. D. Gammell, S. S. Srinivasa, and T. D. Barfoot, “Informed rrt*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,” in 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2014, pp. 2997–3004
2014
Cited alongside, same era.
J. Schulman, Y. Duan, J. Ho, A. Lee, I. Awwal, H. Bradlow, J. Pan, S. Patil, K. Goldberg, and P. Abbeel, “Motion planning with sequential convex optimization and convex collision checking,” The International Journal of Robotics Research , vol. 33, no. 9, pp. 1251–1270, 2014
2014
Cited alongside, same era.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: a simple way to prevent neural networks from overfitting,” The journal of machine learning research , vol. 15, no. 1, pp. 1929–1958, 2014
2014
Cited alongside, same era.
2018
Later among the works it cites.
Z. Kingston, M. Moll, and L. E. Kavraki, “Sampling-based methods for motion planning with constraints,” Annual review of control, robotics, and autonomous systems , vol. 1, pp. 159–185, 2018
2018
Later among the works it cites.
B. Ichter, J. Harrison, and M. Pavone, “Learning sampling distributions for robot motion planning,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 7087–7094
2018
Later among the works it cites.
A. H. Qureshi and M. C. Yip, “Deeply informed neural sampling for robot motion planning,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 6582–6588
2018
Later among the works it cites.
R. Bordalba, L. Ros, and J. M. Porta, “Randomized kinodynamic planning for constrained systems,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 7079–7086
2018
Later among the works it cites.
D. Xu, S. Nair, Y. Zhu, J. Gao, A. Garg, L. Fei-Fei, and S. Savarese, “Neural task programming: Learning to generalize across hierarchical tasks,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 1–8
2018
Later among the works it cites.
C. Zhang, W. Luo, and R. Urtasun, “Efficient convolutions for real-time semantic segmentation of 3d point clouds,” in 2018 International Conference on 3D Vision (3DV) . IEEE, 2018, pp. 399–408
2018
Later among the works it cites.
A. Creswell, T. White, V. Dumoulin, K. Arulkumaran, B. Sengupta, and A. A. Bharath, “Generative adversarial networks: An overview,” IEEE Signal Processing Magazine , vol. 35, no. 1, pp. 53–65, 2018
2018
Later among the works it cites.
A. H. Qureshi, A. Simeonov, M. J. Bency, and M. C. Yip, “Motion planning networks,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 2118–2124
2019
Later among the works it cites.
M. J. Bency, A. H. Qureshi, and M. C. Yip, “Neural path planning: Fixed time, near-optimal path generation via oracle imitation,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2019, pp. 3965–3972
2019
Later among the works it cites.
B. Ichter and M. Pavone, “Robot motion planning in learned latent spaces,” IEEE Robotics and Automation Letters , vol. 4, no. 3, pp. 2407–2414, 2019
2019
Later among the works it cites.
Z. Kingston, M. Moll, and L. E. Kavraki, “Exploring implicit spaces for constrained sampling-based planning,” The International Journal of Robotics Research , vol. 38, no. 10-11, pp. 1151–1178, 2019
2019
Later among the works it cites.
R. Bonalli, A. Cauligi, A. Bylard, T. Lew, and M. Pavone, “Trajectory optimization on manifolds: A theoretically-guaranteed embedded sequential convex programming approach,” in Proceedings of Robotics: Science and Systems , FreiburgimBreisgau, Germany, June 2019
2019
Later among the works it cites.
T. Takayanagi, Y. Kurose, and T. Harada, “Hierarchical task planning from object goal state for human-assist robot,” in 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) . IEEE, 2019, pp. 1359–1366
2019
Later among the works it cites.
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga et al. , “Pytorch: An imperative style, high-performance deep learning library,” in Advances in neural information processing systems , 2019, pp. 8026–8037
2019
Later among the works it cites.
A. H. Qureshi, Y. Miao, A. Simeonov, and M. C. Yip, “Motion planning networks: Bridging the gap between learning-based and classical motion planners,” IEEE Transactions on Robotics , pp. 1–19, 2020
2020
Closest in time.
J. J. Johnson, L. Li, F. Liu, A. H. Qureshi, and M. C. Yip, “Dynamically constrained motion planning networks for non-holonomic robots,” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2020
2020
Closest in time.
A. H. Qureshi, J. Dong, A. Choe, and M. C. Yip, “Neural manipulation planning on constraint manifolds,” IEEE Robotics and Automation Letters , vol. 5, no. 4, pp. 6089–6096, 2020
2020
Closest in time.