The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Toward Robotic Manipulation
Open accessAbstract
This article surveys manipulation, including both biological and robotic manipulation. Biology inspires robotics and demonstrates aspects of manipulation that are far in the future of robotics. Robotics develops concepts and principles that become evident only in the creative process. Robotics also provides a test of our understanding. As Richard Feynman put it: “What I cannot create, I do not understand.”
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Citations
Cites
The information capacity of the human motor system in controlling the amplitude of movement.
Fitts, P. M. (1954) · Journal of Experimental Psychology · doi:10.1037/h0055392 · Cited by 6,466 · cited 1×
“Psychologists use tapping to explore human capabilities (152).”
BackgroundProbabilistic roadmaps for path planning in high-dimensional configuration spaces
Kavraki, L. E., Svestka, P., Latombe, J.-C., & Overmars, M. H. (1996) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.508439 · Cited by 6,343
Genetic Algorithms and Machine Learning
Goldberg, D. E., & Holland, J. H. (1988) · Machine Learning · doi:10.1023/a:1022602019183 · Cited by 3,193
Birglen, L., Laliberté, T., & Gosselin, C. (2008) · Springer Tracts in Advanced Robotics · doi:10.1007/978-3-540-77459-4 · Cited by 572
Analysis and Observations From the First Amazon Picking Challenge
Correll, N., Bekris, K. E., Berenson, D., Brock, O., Causo, A., Hauser, K., Okada, K., Rodriguez, A., Romano, J. M., & Wurman, P. R. (2018) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2016.2600527 · Cited by 425 · cited 1×
“Recent challenges and demonstrations include the Defense Advanced Research Projects Agency (DARPA) Autonomous Robotic Manipulation (ARM) program (70), the DARPA Robotics Challenge (71), and the Amazon Picking Challenge (72), each of which seems to convey the same message: Robotic manipulation has come a long way, yet…”
BackgroundMaitin-Shepard, J., Cusumano-Towner, M., Lei, J., & Abbeel, P. (2010) · 2010 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.2010.5509439 · Cited by 418
Collective Robotics: From Social Insects to Robots
Kube, C. R., & Zhang, H. (1993) · Adaptive Behavior · doi:10.1177/105971239300200204 · Cited by 338
Napier, J. (1993) · doi:10.1515/9781400845910 · Cited by 198
Cited by
Low‐carbon transition risks for finance
Semieniuk, G., Campiglio, E., Mercure, J., Volz, U., & Edwards, N. R. (2021) · WIREs Climate Change · doi:10.1002/wcc.678 · Cited by 441
A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation
Han, D., Mulyana, B., Stankovic, V., & Cheng, S. (2023) · Sensors · doi:10.3390/s23073762 · Cited by 253
A Dexterous Soft Robotic Hand for Delicate In-Hand Manipulation
Abondance, S., Teeple, C. B., & Wood, R. J. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.3007411 · Cited by 253
Rearrangement: A Challenge for Embodied AI
Batra, D., Chang, A. X., Chernova, S., Davison, A. J., Deng, J., Koltun, V., Levine, S., Malik, J., Mordatch, I., Mottaghi, R., et al. (2020) · arXiv · doi:10.48550/arxiv.2011.01975 · Cited by 109
“Grasping and manipulation are rich research areas within robotics [54, 51].”
BackgroundMotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets
Chamzas, C., Quintero-Pena, C., Kingston, Z., Orthey, A., Rakita, D., Gleicher, M., Toussaint, M., & Kavraki, L. E. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3133603 · Cited by 59
Metadata
- Authors
- Mason, M. T.
- Venue
- Annual Review of Control, Robotics, and Autonomous Systems
- Publisher
- Annual Reviews
- Published
- 2018-05-28
- Volume
- 1
- Issue
- 1
- Pages
- 1-28
- ISSN
- 2573-5144 (ISSN-L)
- OpenAlex
- W2789839425
- Cited by
- 182
- References
- 8
- FWCI
- 4.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Mason, M. T. (2018). Toward Robotic Manipulation. Annual Review of Control, Robotics, and Autonomous Systems. https://doi.org/10.1146/annurev-control-060117-104848
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
