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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Integrated task and motion planning in belief space
Leslie Pack Kaelbling, Tomás Lozano‐Pérez
The International Journal of Robotics Research (2013) Vol. 32, Iss. 9-10, pp. 1194-1227
Open Access | Times Cited: 321

Showing 1-25 of 321 citing articles:

Integrated Task and Motion Planning
Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, et al.
Annual Review of Control Robotics and Autonomous Systems (2021) Vol. 4, Iss. 1, pp. 265-293
Open Access | Times Cited: 248
AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers
Yongchao Chen, Jacob Arkin, Charles Dawson, et al.
(2024), pp. 6695-6702
Open Access | Times Cited: 18
Incremental Task and Motion Planning: A Constraint-Based Approach
Neil T. Dantam, Zachary Kingston, Swarat Chaudhuri, et al.
(2016)
Open Access | Times Cited: 162
Planning in the continuous domain: A generalized belief space approach for autonomous navigation in unknown environments
Vadim Indelman, Luca Carlone, Frank Dellaert
The International Journal of Robotics Research (2015) Vol. 34, Iss. 7, pp. 849-882
Open Access | Times Cited: 147
Autonomous multilateral debridement with the Raven surgical robot
Ben Kehoe, Gregory Kahn, Jeffrey Mahler, et al.
(2014), pp. 1432-1439
Open Access | Times Cited: 115
An incremental constraint-based framework for task and motion planning
Neil T. Dantam, Zachary Kingston, Swarat Chaudhuri, et al.
The International Journal of Robotics Research (2018) Vol. 37, Iss. 10, pp. 1134-1151
Open Access | Times Cited: 114
Towards Blended Reactive Planning and Acting using Behavior Trees
Michele Colledanchise, Diogo Almeida, Petter Ögren
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 8839-8845
Open Access | Times Cited: 105
Online Replanning in Belief Space for Partially Observable Task and Motion Problems
Caelan Reed Garrett, Chris Paxton, Tomás Lozano‐Pérez, et al.
(2020), pp. 5678-5684
Open Access | Times Cited: 79
Learning compositional models of robot skills for task and motion planning
Zi Wang, Caelan Reed Garrett, Leslie Pack Kaelbling, et al.
The International Journal of Robotics Research (2021) Vol. 40, Iss. 6-7, pp. 866-894
Open Access | Times Cited: 68
Partially Observable Markov Decision Processes in Robotics: A Survey
Mikko Lauri, David Hsu, Joni Pajarinen
IEEE Transactions on Robotics (2022) Vol. 39, Iss. 1, pp. 21-40
Open Access | Times Cited: 62
The Design of Stretch: A Compact, Lightweight Mobile Manipulator for Indoor Human Environments
Charles C. Kemp, Aaron Edsinger, Henry Clever, et al.
2022 International Conference on Robotics and Automation (ICRA) (2022), pp. 3150-3157
Open Access | Times Cited: 50
Scaling up Gaussian Belief Space Planning Through Covariance-Free Trajectory Optimization and Automatic Differentiation
Sachin Patil, Gregory Kahn, Michael Laskey, et al.
Springer tracts in advanced robotics (2015), pp. 515-533
Closed Access | Times Cited: 80
Geometric backtracking for combined task and motion planning in robotic systems
Julien Bidot, Lars Karlsson, Fabien Lagriffoul, et al.
Artificial Intelligence (2015) Vol. 247, pp. 229-265
Open Access | Times Cited: 64
Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments
Jinhwi Lee, Younggil Cho, Changjoo Nam, et al.
2022 International Conference on Robotics and Automation (ICRA) (2019), pp. 183-189
Open Access | Times Cited: 54
Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics
Corrado Pezzato, Carlos Hernández, Stefan Bonhof, et al.
IEEE Transactions on Robotics (2023) Vol. 39, Iss. 2, pp. 1050-1069
Open Access | Times Cited: 19
Recent Trends in Task and Motion Planning for Robotics: A Survey
Huihui Guo, Fan Wu, Yunchuan Qin, et al.
ACM Computing Surveys (2023) Vol. 55, Iss. 13s, pp. 1-36
Closed Access | Times Cited: 19
Pre- and post-contact policy decomposition for planar contact manipulation under uncertainty
Michael C. Koval, Nancy S. Pollard, Siddhartha S Srinivasa
The International Journal of Robotics Research (2015) Vol. 35, Iss. 1-3, pp. 244-264
Open Access | Times Cited: 59
Mixed Logical Inference and Probabilistic Planning for Robots in Unreliable Worlds
Shiqi Zhang, Mohan Sridharan, Jeremy Wyatt
IEEE Transactions on Robotics (2015) Vol. 31, Iss. 3, pp. 699-713
Open Access | Times Cited: 57
Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions
Shayegan Omidshafiei, Ali‐akbar Agha‐mohammadi, Christopher Amato, et al.
The International Journal of Robotics Research (2017) Vol. 36, Iss. 2, pp. 231-258
Closed Access | Times Cited: 55
Multi-robot grasp planning for sequential assembly operations
Mehmet R. Doğar, Andrew Spielberg, Stuart Baker, et al.
Autonomous Robots (2018) Vol. 43, Iss. 3, pp. 649-664
Open Access | Times Cited: 55
REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics
Mohan Sridharan, Michael Gelfond, Shiqi Zhang, et al.
Journal of Artificial Intelligence Research (2019) Vol. 65, pp. 87-180
Open Access | Times Cited: 52
Provably safe robot navigation with obstacle uncertainty
Brian Axelrod, Leslie Pack Kaelbling, Tomás Lozano‐Pérez
The International Journal of Robotics Research (2018) Vol. 37, Iss. 13-14, pp. 1760-1774
Open Access | Times Cited: 49
Personalized collaborative plans for robot-assisted dressing via optimization and simulation
Ariel Kapusta, Zackory Erickson, Henry Clever, et al.
Autonomous Robots (2019) Vol. 43, Iss. 8, pp. 2183-2207
Open Access | Times Cited: 48
A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain–computer interfacing
D. Kuhner, Lukas D. J. Fiederer, J. Aldinger, et al.
Robotics and Autonomous Systems (2019) Vol. 116, pp. 98-113
Open Access | Times Cited: 45
Learning to guide task and motion planning using score-space representation
Beomjoon Kim, Zi Wang, Leslie Pack Kaelbling, et al.
The International Journal of Robotics Research (2019) Vol. 38, Iss. 7, pp. 793-812
Open Access | Times Cited: 45
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