Open Access Helper

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:

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

Showing 26-50 of 45 citing articles:

A Survey on the Integration of Machine Learning with Sampling-based Motion Planning
Troy McMahon, Aravind Sivaramakrishnan, Edgar Granados, et al.
Foundations and Trends in Robotics (2022) Vol. 9, Iss. 4, pp. 266-327
Open Access | Times Cited: 5
Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs
Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 6
Using Experience to Improve Constrained Planning on Foliations for Multi-Modal Problems
Zachary Kingston, Constantinos Chamzas, Lydia E. Kavraki
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2021), pp. 6922-6927
Closed Access | Times Cited: 6
Sampling-Based Planning for Retrieving Near-Cylindrical Objects in Cluttered Scenes Using Hierarchical Graphs
Hao Tian, Chaoyang Song, Changbo Wang, et al.
IEEE Transactions on Robotics (2022) Vol. 39, Iss. 1, pp. 165-182
Closed Access | Times Cited: 4
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image.
Danny Driess, Jung-Su Ha, Marc Toussaint
(2020)
Closed Access | Times Cited: 5
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning
Troy McMahon, Aravind Sivaramakrishnan, Edgar Granados, et al.
(2022)
Open Access | Times Cited: 3
Planning Rational Behavior of Cognitive Semiotic Agents in a Dynamic Environment
Gennady Osipov, Aleksandr I. Panov
Scientific and Technical Information Processing (2021) Vol. 48, Iss. 6, pp. 502-516
Closed Access | Times Cited: 4
Anticipatory Planning: Improving Long-Lived Planning by Estimating Expected Cost of Future Tasks
Roshan Dhakal, Md Ridwan Hossain Talukder, G. Stein
(2023)
Open Access | Times Cited: 1
Mission Planning for Underwater Survey with Autonomous Marine Vehicles
Junwoo Jang, Haggi Do, Jinwhan Kim
Journal of Ocean Engineering and Technology (2022) Vol. 36, Iss. 1, pp. 41-49
Open Access | Times Cited: 2
NeRP: Neural Rearrangement Planning for Unknown Objects
Ahmed H. Qureshi, Arsalan Mousavian, Chris Paxton, et al.
(2021)
Closed Access | Times Cited: 2
Automatic prior selection for meta Bayesian optimization with a case study on tuning deep neural network optimizers.
Zi Wang, George E. Dahl, Kevin Swersky, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 2
Hierarchical Task and Motion Planning through Deep Reinforcement Learning
Abdullah Al Redwan Newaz, Tauhidul Alam
(2021), pp. 100-105
Closed Access | Times Cited: 2
Policy-Guided Lazy Search with Feedback for Task and Motion Planning
M. N. M. KHODEIR, Atharv Sonwane, Ruthrash Hari, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 1
Control of a Robot Expressive Movements Using Non-Verbal Features
Pablo Osorio, Gentiane Venture
IFAC-PapersOnLine (2022) Vol. 55, Iss. 38, pp. 92-97
Open Access | Times Cited: 1
Simultaneous Action and Grasp Feasibility Prediction for Task and Motion Planning Through Multi-Task Learning
Smail Ait Bouhsain, Rachid Alami, Thierry Siméon
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2023), pp. 2042-2048
Open Access
A Review of Classical and Learning Based Approaches in Task and Motion Planning
Kai Zhang, Eric Lucet, Julien Alexandre Dit Sandretto, et al.
Lecture notes in networks and systems (2023), pp. 83-99
Closed Access
State Representation Learning for Task and Motion Planning in Robot Manipulation
Qu Weiming, Yaoyao Wei, Dingsheng Luo
(2023), pp. 93-99
Closed Access
Designing Human-Robot Coexistence Space
Jixuan Zhi, Lap-Fai Yu, Jyh‐Ming Lien
arXiv (Cornell University) (2020)
Open Access
Reconstructing Interactive 3D Scenes by Panoptic Mapping and CAD Model Alignments
Muzhi Han, Zeyu Zhang, Ziyuan Jiao, et al.
arXiv (Cornell University) (2021)
Open Access
Geometric Task Networks: Learning Efficient and Explainable Skill Coordination for Object Manipulation
Meng Guo, Mathias Bürger
arXiv (Cornell University) (2021)
Open Access
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