Robot task planning and explanation in open and uncertain worlds
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Mitigating undesirable bias to achieve fairness might require an explicit instruction to the artificial learning engine including rules of appropriate conduct, as proposed in cognitive robotics.
“Mitigating undesirable bias to achieve fairness might require an explicit instruction to the artificial learning engine including rules of appropriate conduct, as proposed in the domain of cognitive robotics117.”
From Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare (2020) · cites this paper as [117]
Cites
An extended set of Haar-like features for rapid object detection
Lienhart, R., & Maydt, J. (2003) · Proceedings. International Conference on Image Processing · doi:10.1109/icip.2002.1038171 · Cited by 2,977 · cited 1× · see citing works
“For each view acquired, the OpenCV face detector (using cascades of simple detectors for simple Haar-like features [28]) is run to yield a number of potential faces.”
MethodProceedings of 1995 IEEE International Conference on Robotics and Automation
(1995) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1995.525251 · Cited by 2,845 · see citing works
A theory of diagnosis from first principles
Reiter, R. (1987) · Artificial Intelligence · doi:10.1016/0004-3702(87)90062-2 · Cited by 1,987 · see citing works
The Fast Downward Planning System
Helmert, M. (2006) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1705 · Cited by 1,479 · see citing works
Explanation-Based Generalization: A Unifying View
Mitchell, T. M., Keller, R. M., & Kedar-Cabelli, S. T. (1986) · Machine Learning · doi:10.1023/a:1022691120807 · Cited by 1,382 · see citing works
The Fast Downward Planning System
Helmert, M. (2006) · Cited by 1,222 · see citing works
Towards robotic assistants in nursing homes: Challenges and results
Pineau, J., Montemerlo, M., Pollack, M., Roy, N., & Thrun, S. (2003) · Robotics and Autonomous Systems · doi:10.1016/s0921-8890(02)00381-0 · Cited by 640 · see citing works
Experiences with an architecture for intelligent, reactive agents
Bonasso, R. P., Firby, R. J., Gat, E., Kortenkamp, D. M., Miller, D., & Slack, M. G. (1997) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/095281397147103 · Cited by 606 · see citing works
COMPLEXITY RESULTS FOR SAS+ PLANNING
Bäckström, C., & Nebel, B. (1995) · Computational Intelligence · doi:10.1111/j.1467-8640.1995.tb00052.x · Cited by 399 · see citing works
KNOWROB — knowledge processing for autonomous personal robots
Tenorth, M., & Beetz, M. (2009) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2009.5354602 · Cited by 301 · see citing works
Conceptual spatial representations for indoor mobile robots
Zender, H., Mozos, Ó. M., Jensfelt, P., Kruijff, G.-J., & Burgard, W. (2008) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2008.03.007 · Cited by 298 · see citing works
Self-citationGerevini, A., Haslum, P., Long, D. P., Saetti, A., & Dimopoulos, Y. (2008) · Artificial Intelligence · doi:10.1016/j.artint.2008.10.012 · Cited by 294 · see citing works
Robot task planning using semantic maps
Galindo, C., Fernández‐Madrigal, J., González, J., & Saffiotti, A. (2008) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2008.08.007 · Cited by 292 · see citing works
Large-scale semantic mapping and reasoning with heterogeneous modalities
Pronobis, A., & Jensfelt, P. (2012) · 2012 IEEE International Conference on Robotics and Automation · doi:10.1109/icra.2012.6224637 · Cited by 248 · see citing works
Self-citationPrediction is deduction but explanation is abduction
Shanahan, M. (1989) · Cited by 247 · see citing works
A randomized art-gallery algorithm for sensor placement
González-Baños, H. H. (2001) · Annual Symposium on Computational Geometry (SoCG) · doi:10.1145/378583.378674 · Cited by 232 · see citing works
Belief Revisions and the Ramsey Test for Conditionals
Gärdenfors, P. (1986) · The Philosophical Review · doi:10.2307/2185133 · Cited by 229 · see citing works
libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models
Mooij, J. M. (2010) · Max Planck Institute for Plasma Physics · doi:10.5555/1756006.1859925 · Cited by 228 · see citing works
Martinez-Cantin, R., de Freitas, N., Brochu, E., Castellanos, J., & Doucet, A. (2009) · Autonomous Robots · doi:10.1007/s10514-009-9130-2 · Cited by 217 · see citing works
A layered architecture for office delivery robots
Simmons, R. G., Goodwin, R., Haigh, K. Z., Koenig, S., & O’Sullivan, J. A. (1997) · doi:10.1145/267658.267723 · Cited by 196 · see citing works
A knowledge-based approach to planning with incomplete information and sensing
Petrick, R. P. A., & Bacchus, F. (2002) · Cited by 195 · see citing works
Continual planning and acting in dynamic multiagent environments
Brenner, M., & Nebel, B. (2009) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-009-9081-1 · Cited by 168 · see citing works
Multi-modal Semantic Place Classification
Pronobis, A., Mozos, Ó. M., Barbara Caputo, B., & Jensfelt, P. (2009) · The International Journal of Robotics Research · doi:10.1177/0278364909356483 · Cited by 149 · see citing works
Self-citationPerception as Abduction: Turning Sensor Data Into Meaningful Representation
Shanahan, M. (2005) · Cognitive Science · doi:10.1207/s15516709cog2901_5 · Cited by 135 · see citing works
Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems
(1995) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.1995.525766 · Cited by 121 · see citing works
Active Visual Object Search in Unknown Environments Using Uncertain Semantics
Aydemir, A., Pronobis, A., Göbelbecker, M., & Jensfelt, P. (2013) · IEEE Transactions on Robotics · doi:10.1109/tro.2013.2256686 · Cited by 107 · see citing works
Self-citationUtilizing object-object and object-scene context when planning to find things
Kollar, T., & Roy, N. (2009) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2009.5152831 · Cited by 106 · see citing works
Search in the real world: Active visual object search based on spatial relations
Aydemir, A., Sjöö, K., Folkesson, J. B., Pronobis, A., & Jensfelt, P. (2011) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2011.5980495 · Cited by 102 · see citing works
Self-citationPreferred Explanations: Theory and Generation via Planning
Sohrabi, S., Baier, J. A., & McIlraith, S. A. (2011) · AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v25i1.7845 · Cited by 102 · see citing works
GOAL‐DRIVEN AUTONOMY FOR RESPONDING TO UNEXPECTED EVENTS IN STRATEGY SIMULATIONS
Klenk, M., Molineaux, M., & Aha, D. (2013) · International Conference on Climate Informatics · doi:10.1111/j.1467-8640.2012.00445.x · Cited by 96 · see citing works
Object detection and mapping for service robot tasks
Ekvall, S., Kragić, D., & Jensfelt, P. (2007) · Robotica · doi:10.1017/s0263574706003237 · Cited by 90 · see citing works
Self-citationProceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Fong, T., Dautenhahn, K., Scheutz, M. J., & Demiris, Y. (2008) · doi:10.1145/1349822 · Cited by 89 · see citing works
Planning for human-robot teaming in open worlds
Talamadupula, K., Benton, J., Subbarao Kambhampati, B., Schermerhorn, P., & Scheutz, M. J. (2010) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1869397.1869403 · Cited by 85 · see citing works
Ontology-based multi-layered robot knowledge framework (OMRKF) for robot intelligence
Suh, I. H., Lim, G. H., Hwang, W., Suh, H.-W., Choi, J.-H., & Park, Y.-T. (2007) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2007.4399082 · Cited by 84 · see citing works
Proceedings of the first international conference on Autonomous agents
Johnson, W. L. (1997) · Cited by 74 · see citing works
Proceedings of the 16th Computer Vision Winter Workshop
Wendel, A. (2020) · TUGraz OPEN Library (Graz University of Technology) · doi:10.3217/978-3-85125-141-8 · Cited by 64 · see citing works
Democracia e Cidadania na Escola: Do Discurso à Prática
Antunes, A. L. (2008) · Múltiplas Leituras · doi:10.15603/1982-8993/ml.v1n2p47-66 · Cited by 56 · see citing works
Mixed Logical Inference and Probabilistic Planning for Robots in Unreliable Worlds
Zhang, S., Sridharan, M., & Wyatt, J. (2015) · IEEE Transactions on Robotics · doi:10.1109/tro.2015.2422531 · Cited by 52 · see citing works
Self-citationThe 5th International Conference on Intelligent Autonomous Systems
(2022) · Intelligent Autonomous Systems · doi:10.1109/icoias56028.2022.9931256 · Cited by 48 · see citing works
Exploiting Probabilistic Knowledge under Uncertain Sensing for Efficient Robot Behaviour
Hanheide, M., Gretton, C., Dearden, R., Hawes, N., Wyatt, J., Goedelbecker, M., Pronobis, A., Aydemir, A., & Zender, H. (2011) · Griffith Research Online · doi:10.5591/978-1-57735-516-8/ijcai11-407 · Cited by 47 · see citing works
Self-citationCrossmodal content binding in information-processing architectures
Jacobsson, H., Hawes, N., Kruijff, G.-J. M., & Wyatt, J. (2008) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/1349822.1349834 · Cited by 45 · see citing works
Self-citationPlan-based Object Search and Exploration using Semantic Spatial Knowledge in the Real World.
Aydemir, A., Göbelbecker, M., Pronobis, A., Sjöö, K., & Jensfelt, P. (2011) · Cited by 42 · see citing works
Self-citationEngineering intelligent information-processing systems with CAST
Hawes, N., & Wyatt, J. (2009) · Advanced Engineering Informatics · doi:10.1016/j.aei.2009.08.010 · Cited by 42 · see citing works
Self-citationTopological spatial relations for active visual search
Sjöö, K., Aydemir, A., & Jensfelt, P. (2012) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2012.06.001 · Cited by 41 · see citing works
Self-citationSearching objects in large-scale indoor environments: A decision-theoretic approach
Kunze, L., Beetz, M., Saito, M., Azuma, H., Okada, K., & Inaba, M. (2012) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2012.6224965 · Cited by 41 · see citing works
Equipping robot control programs with first-order probabilistic reasoning capabilities
Jain, D., Mösenlechner, L., & Beetz, M. (2009) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2009.5152676 · Cited by 40 · see citing works
Self-Understanding and Self-Extension: A Systems and Representational Approach
Wyatt, J., Aydemir, A., Brenner, M., Hanheide, M., Hawes, N., Jensfelt, P., Kristan, M., Kruijff, G.-J. M., Lison, P., Pronobis, A., et al. (2010) · IEEE Transactions on Autonomous Mental Development · doi:10.1109/tamd.2010.2090149 · Cited by 38 · see citing works
Self-citationA system for interactive learning in dialogue with a tutor
Skočaj, D., Kristan, M., Vrečko, A., Mahnič, M., Janíček, M., Kruijff, G.-J. M., Hanheide, M., Hawes, N., Keller, T., Zillich, M., et al. (2011) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2011.6094926 · Cited by 37 · see citing works
Self-citationA Switching Planner for Combined Task and Observation Planning
Göbelbecker, M., Gretton, C., & Dearden, R. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v25i1.8011 · Cited by 34 · see citing works
Self-citationSituated resolution and generation of spatial referring expressions for robotic assistants
Zender, H., Kruijff, G.-J. M., & Kruijff‐Korbayová, I. (2009) · Cited by 33 · see citing works
Self-citationA Framework for Goal Generation and Management
Hanheide, M., Hawes, N., Wyatt, J., Göbelbecker, M., Brenner, M., Sjöö, K., Aydemir, A., Jensfelt, P., Zender, H., & Kruijff, G.-J. (2010) · Cited by 32 · see citing works
Self-citationExploration and Planning in a Three-Level Cognitive Architecture
Kraft, D., Başeski, E., Popović, M., Batog, A. M., Kjær‐Nielsen, A., Krüger, N., Petrick, R. P. A., Geib, C., Pugeault, N., Steedman, M. J., et al. (2008) · University of Southern Denmark Research Portal (University of Southern Denmark) · Cited by 24 · see citing works
Home alone: Autonomous extension and correction of spatial representations
Hawes, N., Hanheide, M., Hargreaves, J., Page, B., Zender, H., & Jensfelt, P. (2011) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2011.5980004 · Cited by 22 · see citing works
Self-citationRepresenting Spatial Knowledge in Mobile Cognitive Systems
Pronobis, A., Sjöö, K., Aydemir, A., Bishop, A. N., & Jensfelt, P. (2010) · IOS Press eBooks · doi:10.3233/978-1-60750-613-3-133 · Cited by 18 · see citing works
Self-citationModelling Observation Correlations for Active Exploration and Robust Object Detection
Velez, J., Hemann, G., Huang, A. S., Posner, I., & Roy, N. (2012) · Journal of Artificial Intelligence Research · doi:10.1613/jair.3516 · Cited by 18 · see citing works
Variable resolution decomposition for robotic navigation under a POMDP framework
Kaplow, R., Atrash, A., & Pineau, J. (2010) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2010.5509188 · Cited by 16 · see citing works
Modelling Observation Correlations for Active Exploration and Robust Object Detection
Velez, J. J., Huang, A. S., Hemann, G. A., Roy, N., & Roy, N. (2011) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 14 · see citing works
Architecture and Representations
Hawes, N., Wyatt, J., Sridharan, M., Jacobsson, H., Dearden, R., Sloman, A., & Kruijff, G.-J. M. (2010) · Cognitive systems monographs · doi:10.1007/978-3-642-11694-0_2 · Cited by 14 · see citing works
Self-citationSjöö, K., Zender, H., Jensfelt, P., Kruijff, G.-J. M., Pronobis, A., Hawes, N., & Brenner, M. (2010) · Cognitive systems monographs · doi:10.1007/978-3-642-11694-0_10 · Cited by 12 · see citing works
Self-citationA framework for robust cognitive spatial mapping
Pronobis, A., Sjöö, K., Aydemir, A., Bishop, A. N., & Jensfelt, P. (2009) · Cited by 11 · see citing works
Self-citationAbductive Reasoning for Continual Dialogue Understanding
Janíček, M. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31467-4_2 · Cited by 11 · see citing works
New Directions in Logic, Language and Computation
Lassiter, D., & Slavkovik, M. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31467-4 · Cited by 11 · see citing works
Abductive Reasoning for Continual Dialogue Understanding.
Janíček, M. (2011) · Cited by 7 · see citing works
Flagged first, then by citations
4 of the 68 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Semantics derived automatically from language corpora contain human-like biases
Caliskan, A., Bryson, J. J., & Narayanan, A. (2017) · Science · doi:10.1126/science.aal4230 · Cited by 2,887 · see citing works
Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare
Cirillo, D., Catuara-Solarz, S., Morey, C., Guney, E., Subirats, L., Mellino, S., Gigante, A., Valencia, A., Rementeria, M. J., Chadha, A. S., et al. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0288-5 · Cited by 553 · see citing works
Towards a science of integrated AI and Robotics
Rajan, K., & Saffiotti, A. (2017) · Artificial Intelligence · doi:10.1016/j.artint.2017.03.003 · Cited by 180 · see citing works
Plan explicability and predictability for robot task planning
Zhang, Y., Sreedharan, S., Kulkarni, A., Chakraborti, T., Zhuo, H. H., & Subbarao Kambhampati, B. (2017) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2017.7989155 · Cited by 137 · see citing works
A vision chip with complementary pathways for open-world sensing
Yang, Z., Wang, T., Lin, Y., Chen, Y., Zeng, H., Pei, J., Wang, J., Liu, X., Zhou, Y., Zhang, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07358-4 · Cited by 110 · see citing works
Kim, U.-H., Park, J.-M., Song, T.-J., & Kim, J.-H. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2019.2931042 · Cited by 109 · see citing works
The Emerging Landscape of Explainable Automated Planning & Decision Making
Chakraborti, T., Sreedharan, S., & Subbarao Kambhampati, B. (2020) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2020/669 · Cited by 107 · see citing works
Taxonomy of Trust-Relevant Failures and Mitigation Strategies
Tolmeijer, S., Weiss, A., Hanheide, M., Lindner, F., Powers, T. M., Dixon, C., & Tielman, M. L. (2020) · Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction · doi:10.1145/3319502.3374793 · Cited by 103 · see citing works
Self-citationSDRL: Interpretable and Data-Efficient Deep Reinforcement Learning Leveraging Symbolic Planning
Lyu, D., Yang, F., Liu, B., & Gustafson, S. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33012970 · Cited by 103 · see citing works
Yang, F., Lyu, D., Liu, B., & Gustafson, S. (2018) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2018/675 · Cited by 103 · see citing works
Cao, R., Li, S., Ji, Y., Zhang, Z., Xu, H., Zhang, M., Li, M., & Li, H. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2021.105993 · Cited by 98 · see citing works
Explanations and trust: What happens to trust when a robot partner does something unexpected?
Lyons, J. B., Hamdan, I. A., & Vo, T. Q. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107473 · Cited by 97 · see citing works
Scheduling of smart intra – factory material supply operations using mobile robots
Kousi, N., Koukas, S., Michalos, G., & Makris, S. (2018) · International Journal of Production Research · doi:10.1080/00207543.2018.1483587 · Cited by 83 · see citing works
Survey on robotic systems for internal logistics
Bernardo, R. M. C., Sousa, J. M. C., & Gonçalves, P. J. S. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.09.014 · Cited by 80 · see citing works
Integrating action knowledge and LLMs for task planning and situation handling in open worlds
Ding, Y. F., Zhang, X., Amiri, S., Cao, N., Yang, H., Kaminski, A., Esselink, C., & Zhang, S. (2023) · Autonomous Robots · doi:10.1007/s10514-023-10133-5 · Cited by 71 · see citing works
Explainable reinforcement learning for broad-XAI: a conceptual framework and survey
Dazeley, R., Vamplew, P. W., & Cruz, F. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-08423-1 · Cited by 68 · see citing works
Probabilistic planning with formal performance guarantees for mobile service robots
Lacerda, B., Faruq, F., Parker, D., & Hawes, N. (2019) · The International Journal of Robotics Research · doi:10.1177/0278364919856695 · Cited by 64 · see citing works
Self-citationFrom Automation System to Autonomous System: An Architecture Perspective
Chen, H., Wen, Y., Zhu, M., Huang, Y., Xiao, C., Wei, T., & Hahn, A. (2021) · Journal of Marine Science and Engineering · doi:10.3390/jmse9060645 · Cited by 53 · see citing works
Reasoning With Scene Graphs for Robot Planning Under Partial Observability
Amiri, S., Chandan, K., & Zhang, S. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3157567 · Cited by 50 · see citing works
Wang, Z., & Tian, G. (2022) · Information Sciences · doi:10.1016/j.ins.2022.01.058 · Cited by 33 · see citing works
Short-Term Human-Robot Interaction through Conditional Planning and Execution
Sanelli, V., Cashmore, M., Magazzeni, D., & Iocchi, L. (2017) · Proceedings of the International Conference on Automated Planning and Scheduling · doi:10.1609/icaps.v27i1.13864 · Cited by 32 · see citing works
AI based combined scheduling and motion planning in flexible robotic assembly lines
Kousi, N., Dimosthenopoulos, D., Matthaiakis, A.-S., Michalos, G., & Makris, S. (2019) · Procedia CIRP · doi:10.1016/j.procir.2020.01.041 · Cited by 31 · see citing works
Designing Up with Value-Sensitive Design: Building a Field Guide for Ethical ML Development
Boyd, K. (2022) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3531146.3534626 · Cited by 30 · see citing works
A Framework for Service Robots in Smart Home: An Efficient Solution for Domestic Healthcare
Ramoly, N., Bouzeghoub, A., & Finance, B. (2018) · IRBM · doi:10.1016/j.irbm.2018.10.010 · Cited by 30 · see citing works
Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic Maps
Zheng, K., Pronobis, A., & Rao, R. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11743 · Cited by 28 · see citing works
Self-citationHecksteden, A., Keller, N., Zhang, G., Meyer, T., & Hauser, T. (2023) · Sports Medicine - Open · doi:10.1186/s40798-023-00641-0 · Cited by 25 · see citing works
Dynamically Constructed (PO)MDPs for Adaptive Robot Planning
Zhang, S., Khandelwal, P., & Stone, P. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v31i1.11042 · Cited by 25 · see citing works
Balancing Explicability and Explanation in Human-Aware PlanningPreprint
Chakraborti, T., Sreedharan, S., & Subbarao Kambhampati, B. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1708.00543 · Cited by 24 · see citing works
Yang, G., Wang, S., Okamura, H., Shen, B., Ueda, Y., Yasui, T., Yamada, T., Miyazawa, Y., Yoshida, S., Inada, Y., et al. (2021) · Automation in Construction · doi:10.1016/j.autcon.2021.103758 · Cited by 23 · see citing works
TDM: Trustworthy Decision-Making Via Interpretability Enhancement
Lyu, D., Yang, F., Kwon, H., Dong, W., Yılmaz, L., & Liu, B. (2021) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2021.3084290 · Cited by 23 · see citing works
Open-World Reasoning for Service Robots
Jiang, Y., Walker, N., Hart, J., & Stone, P. (2019) · Proceedings of the International Conference on Automated Planning and Scheduling · doi:10.1609/icaps.v29i1.3541 · Cited by 23 · see citing works
Bernardo, R. M. C., Sousa, J. M. C., & Gonçalves, P. J. S. (2023) · Computers & Industrial Engineering · doi:10.1016/j.cie.2023.109345 · Cited by 22 · see citing works
Robust and efficient task scheduling for robotics applications with reinforcement learning
Tejer, M., Szczepański, R., & Tarczewski, T. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.107300 · Cited by 22 · see citing works
Online Explanation Generation for Planning Tasks in Human-Robot Teaming
Zakershahrak, M., Gong, Z., Sadassivam, N., & Zhang, Y. (2020) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341792 · Cited by 22 · see citing works
Wang, B., Yuan, T., & Rau, P. P. (2024) · International Journal of Social Robotics · doi:10.1007/s12369-024-01132-2 · Cited by 21 · see citing works
From Pixels to Buildings: End-to-end Probabilistic Deep Networks for Large-scale Semantic Mapping
Zheng, K., & Pronobis, A. (2019) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros40897.2019.8967568 · Cited by 21 · see citing works
Self-citationExpect the Unexpected: Leveraging the Human-Robot Ecosystem to Handle Unexpected Robot Failures
Honig, S., & Oron-Gilad, T. (2021) · Frontiers in Robotics and AI · doi:10.3389/frobt.2021.656385 · Cited by 20 · see citing works
BackMix: Regularizing Open Set Recognition by Removing Underlying Fore-Background Priors
Wang, Y., Mu, J., Huang, H., Wang, Q., Zhu, P., & Hu, Q. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3550703 · Cited by 19 · see citing works
Knowledge-Based Hierarchical POMDPs for Task Planning
Serrano, S. A., Santiago, E., Martínez-Carranza, J., Morales, E. F., & Sucar, L. E. (2021) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-021-01348-8 · Cited by 18 · see citing works
A survey of Semantic Reasoning frameworks for robotic systems
Liu, W., Daruna, A., Patel, M., Ramachandruni, K., & Chernova, S. (2022) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2022.104294 · Cited by 18 · see citing works
A Novelty-Centric Agent Architecture for Changing Worlds.
Faizan, M., Sarathy, V., Tatiya, G., Goel, S., Gyawali, S., Castro, M. G., Sinapov, J., & Scheutz, M. J. (2021) · Autonomous Agents and Multi-Agent Systems · Cited by 16 · see citing works
A survey of knowledge‐based sequential decision‐making under uncertainty
Zhang, S., & Sridharan, M. (2022) · AI Magazine · doi:10.1002/aaai.12053 · Cited by 16 · see citing works
Extracting general task structures to accelerate the learning of new tasks
Dianov, I., Ramírez-Amaro, K., Lanillos, P., Dean‐Leon, E., Bergner, F., & Cheng, G. (2016) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids.2016.7803365 · Cited by 15 · see citing works
REX: Designing User-centered Repair and Explanations to Address Robot Failures
Lee, C. P., Praveena, P., & Mutlu, B. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661559 · Cited by 15 · see citing works
Planning with task-oriented knowledge acquisition for a service robot
Chen, K., Yang, F., & Chen, X. (2016) · International Joint Conference on Artificial Intelligence · Cited by 15 · see citing works
Integrating Answer Set Programming with Semantic Dictionaries for Robot Task Planning
Lu, D., Zhou, Y., Wu, F., Zhang, Z., & Chen, X. (2017) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2017/609 · Cited by 15 · see citing works
LAAIR: A Layered Architecture for Autonomous Interactive RobotsPreprint
Jiang, Y., Walker, N., Kim, M., Brissonneau, N., Brown, D. S., Hart, J., Niekum, S., Sentis, L., & Stone, P. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.03563 · Cited by 15 · see citing works
Planning Beyond The Sensing Horizon Using a Learned Context
Everett, M., Miller, J., & How, J. P. (2019) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros40897.2019.8967550 · Cited by 14 · see citing works
Answerable and Unanswerable Questions in Risk Analysis with Open‐World Novelty
Cox, L. A. (2020) · Risk Analysis · doi:10.1111/risa.13553 · Cited by 14 · see citing works
A Practical Framework for Robust Decision-Theoretic Planning and Execution for Service Robots
Iocchi, L., Jeanpierre, L., Lázaro, M. T., & Mouaddib, A. (2016) · Proceedings of the International Conference on Automated Planning and Scheduling · doi:10.1609/icaps.v26i1.13790 · Cited by 14 · see citing works
SO-MRS: A Multi-robot System Architecture Based on the SOA Paradigm and Ontology
Skarżyński, K., Stępniak, M., Bartyna, W., & Ambroszkiewicz, S. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-96728-8_28 · Cited by 14 · see citing works
Desire-Driven Reasoning for Personal Care Robots
Yang, G., Wang, S., & Yang, J. (2019) · IEEE Access · doi:10.1109/access.2019.2921112 · Cited by 14 · see citing works
REBA: A Refinement-Based Architecture for Knowledge Representation and Reasoning in Robotics
Sridharan, M., Gelfond, M., Zhang, S., & Wyatt, J. (2019) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.11524 · Cited by 13 · see citing works
Self-citationOntological framework for high-level task replanning for autonomous robotic systems
Bernardo, R., Sousa, J. M. C., & Gonçalves, P. J. S. (2024) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2024.104861 · Cited by 13 · see citing works
Towards Robust One-shot Task Execution using Knowledge Graph Embeddings
Daruna, A., Nair, L., Liu, W., & Chernova, S. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9561782 · Cited by 13 · see citing works
A Bayesian based Methodology for Indirect Object Search
Loncomilla, P., Ruíz-del-Solar, J., & Saavedra, M. (2017) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-017-0643-1 · Cited by 13 · see citing works
Task motion planning for anthropomorphic arms based on human arm movement primitives
Gong, S., Zhao, J., Zhang, Z., & Xie, B. (2020) · Industrial Robot the international journal of robotics research and application · doi:10.1108/ir-12-2019-0261 · Cited by 13 · see citing works
A Unified Topological Representation for Robotic Fleets in Agricultural Applications
Das, G. P., Cielniak, G., Heselden, J. R., Pearson, S., Duchetto, F. D., Zhu, Z., Dichtl, J., Hanheide, M., Fentanes, J. P., Binch, A., et al. (2024) · Journal of Field Robotics · doi:10.1002/rob.22494 · Cited by 12 · see citing works
Self-citationZhang, S., Jiang, J., He, Z., Zhao, X., & Fang, J. (2019) · IEEE Access · doi:10.1109/access.2019.2931576 · Cited by 12 · see citing works
Semantic Task Planning for Service Robots in Open Worlds
Cui, G., Wei, S., & Chen, X. (2021) · Future Internet · doi:10.3390/fi13020049 · Cited by 12 · see citing works
Order Matters: Generating Progressive Explanations for Planning Tasks in Human-Robot Teaming
Zakershahrak, M., Marpally, S. R., Sharma, A., Gong, Z., & Zhang, Y. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9561762 · Cited by 12 · see citing works
Which tool to use? Grounded reasoning in everyday environments with assistant robots.
Fischer, L., Hasler, S., Deigmoeller, J., Schnuerer, T., Redert, M., Pluntke, U., Nagel, K., Senzel, C., Ploennigs, J., Richter, A., et al. (2018) · Cited by 11 · see citing works
Using knowledge representation and reasoning tools in the design of robots
Sridharan, M., & Gelfond, M. (2016) · University of Birmingham Research Portal (University of Birmingham) · Cited by 10 · see citing works
Baldridge, J., Bedrax-Weiss, T., Luong, D., Narayanan, S., Pang, B., Pereira, F. M. B., Soricut, R., Tseng, M., & Zhang, Y. (2018) · doi:10.18653/v1/w18-1406 · Cited by 10 · see citing works
Sasabuchi, K., Ikeuchi, K., & Inaba, M. (2018) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3173386.3173390 · Cited by 10 · see citing works
BlueSky: Combining Task Planning and Activity-Centric Access Control for Assistive Humanoid Robots
Bayreuther, S., Jacob, F., Grotz, M., Kartmann, R., Peller-Konrad, F., Paus, F., Hannes Hartenstein, B., & Asfour, T. (2022) · ACM Symposium on Access Control Models and Technologies (SACMAT) · doi:10.1145/3532105.3535018 · Cited by 10 · see citing works
Intuitive Programming of Conditional Tasks by Demonstration of Multiple Solutions
Eiband, T., Saveriano, M., & Lee, D. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2935381 · Cited by 10 · see citing works
Bridging Commonsense Reasoning and Probabilistic Planning via a Probabilistic Action Language
Wang, Y., Zhang, S., & LEE, J. (2019) · Theory and Practice of Logic Programming · doi:10.1017/s1471068419000371 · Cited by 10 · see citing works
Monte Carlo Tree Search and GR(1) Synthesis for Robot Tasks Planning in Automotive Production Lines
Wete, E., Greenyer, J., Wortmann, A., Flegel, O., & Klein, M. (2021) · ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) · doi:10.1109/models50736.2021.00039 · Cited by 9 · see citing works
Safe and Efficient Navigation in Extreme Environments using Semantic Belief Graphs
Ginting, M. F., Kim, S. K., Peltzer, O., Ott, J., Jung, S., Kochenderfer, M. J., & Agha–mohammadi, A. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10161056 · Cited by 9 · see citing works
An ambient intelligence approach for learning in smart robotic environments
Bacciu, D., Rocco, M. D., Dragone, M., Gallicchio, C., Micheli, A., & Saffiotti, A. (2019) · Computational Intelligence · doi:10.1111/coin.12233 · Cited by 9 · see citing works
TSM: Topological Scene Map for Representation in Indoor Environment Understanding
Liao, Z., Zhang, Y., Luo, J., & Yuan, W. (2020) · IEEE Access · doi:10.1109/access.2020.3029324 · Cited by 9 · see citing works
Semantic Knowledge-Based Hierarchical Planning Approach for Multi-Robot Systems
Bae, S.-H., Joo, S.-H., Choi, J.-H., Pyo, J., Park, H., & Kuc, T. (2023) · Electronics · doi:10.3390/electronics12092131 · Cited by 8 · see citing works
What do you really want to do? Towards a Theory of Intentions for Human-Robot Collaboration
Gomez, R., Sridharan, M., & Riley, H. (2020) · Annals of Mathematics and Artificial Intelligence · doi:10.1007/s10472-019-09672-4 · Cited by 8 · see citing works
Kim, M., & Suh, I. H. (2019) · Intelligent Service Robotics · doi:10.1007/s11370-019-00288-5 · Cited by 8 · see citing works
Planning robotic agent actions using semantic knowledge for a home environment
Bernardo, R. M. C., Sousa, J. M. C., & Gonçalves, P. J. S. (2021) · Intelligence & Robotics · doi:10.20517/ir.2021.10 · Cited by 8 · see citing works
Systems of natural-language-facilitated human-robot cooperation: A reviewPreprint
Liu, R., & Zhang, X. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1701.08269 · Cited by 8 · see citing works
Task and Motion Planning for Execution in the Real
Pan, T., Shome, R., & Kavraki, L. E. (2024) · IEEE Transactions on Robotics · doi:10.1109/tro.2024.3418550 · Cited by 7 · see citing works
Desire-Driven Reasoning Considering Personalized Care Preferences
Yang, G., Wang, S., Yang, J., & Shi, P. J. (2021) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2021.3131338 · Cited by 7 · see citing works
Xi, X., & Zhu, S. (2022) · Artificial Intelligence Review · doi:10.1007/s10462-022-10347-6 · Cited by 7 · see citing works
All about human-robot interaction
Singh, K. J., Kapoor, D. S., & Sohi, B. S. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-85769-7.00010-0 · Cited by 7 · see citing works
A Hierarchical Deliberative Architecture Framework based on Goal Decomposition
Lesire, C., Bailon-Ruiz, R., Barbier, M., & Grand, C. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981488 · Cited by 7 · see citing works
Explainable Robotic Plan Execution Monitoring Under Partial Observability
Çoruhlu, G., Erdem, E., & Patoğlu, V. (2021) · IEEE Transactions on Robotics · doi:10.1109/tro.2021.3123840 · Cited by 6 · see citing works
Building Plannable Representations with Mixed Reality
Rosen, E., Kumar, N., Gopalan, N., Ullman, D. L., Konidaris, G., & Tellex, S. (2020) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros45743.2020.9341627 · Cited by 6 · see citing works
Desiderata for Planning Systems in General-Purpose Service RobotsPreprint
Walker, N., Jiang, Y., Çakmak, M., & Stone, P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.02300 · Cited by 6 · see citing works
Zakershahrak, M., & Ghodratnama, S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.11792 · Cited by 6 · see citing works
Chapter 5 Robotics as an Enabler of Resiliency to Disasters: Promises and Pitfalls
Wang, R., Nakhimovich, D., Roberts, F. S., & Bekris, K. E. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-70370-7_5 · Cited by 5 · see citing works
Sridharan, M., & Meadows, B. (2016) · IEEE International Conference on Development and Learning (ICDL) · doi:10.1109/devlrn.2016.7846827 · Cited by 5 · see citing works
Task-Motion Planning System for Socially Viable Service Robots Based on Object Manipulation
Jeon, J., Jung, H.-R., Pico, N., Luong, T. A., & Moon, H. (2024) · Biomimetics · doi:10.3390/biomimetics9070436 · Cited by 5 · see citing works
Natural Language Explanations in Human-Collaborative Systems
Scalise, R., Rosenthal, S. L., & Srinivasa, S. S. (2017) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3029798.3034809 · Cited by 5 · see citing works
Learning and Reasoning for Robot Dialog and Navigation Tasks
Lu, K., Zhang, S., Stone, P., & Chen, X. (2020) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/2020.sigdial-1.14 · Cited by 5 · see citing works
Plan Explainability and Predictability for Cobots.Preprint
Zhang, Y., Zhuo, H. H., & Subbarao Kambhampati, B. (2015) · arXiv (Cornell University) · Cited by 5 · see citing works
Proactive care architecture for care robots
Ren, Z., Yang, G., Wang, S., & Yang, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-14224-4 · Cited by 4 · see citing works
Research Trend Analysis of Multi-Task Behavior Cloning for Robot Manipulation
Park, S.-G., Ahn, W. J., Kang, S.-W., & Lim, M. (2023) · International Conference on Control, Automation and Systems (ICCAS) · doi:10.23919/iccas59377.2023.10316957 · Cited by 4 · see citing works
A Causal Multi-armed Bandit Approach for Domestic Robots’ Failure Avoidance
Ramoly, N., Bouzeghoub, A., & Finance, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-70136-3_10 · Cited by 4 · see citing works
A Robotic Context Query-Processing Framework Based on Spatio-Temporal Context Ontology
Lee, S.-J., & Kim, I. (2018) · Sensors · doi:10.3390/s18103336 · Cited by 4 · see citing works
Designing Interaction for Multi-agent Cooperative System in an Office Environment
Wang, C., Hasler, S., Mühlig, M., Joublin, F., Ceravola, A., Deigmoeller, J., Fischer, L., & An, P. (2021) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3434074.3447277 · Cited by 4 · see citing works
Accelerating spiking neural networks with photonic reconfigurable devices
Lu, C., Xu, K., Liu, J., Ding, Y., Yu, J., Song, J., Meng, J., Wang, T., Guo, S., Jin, X., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-72119-y · Cited by 3 · see citing works
Engaging Learners in Dialogue Interactivity Development for Mobile Robots
Baxter, P. E., Duchetto, F. D., & Hanheide, M. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-18141-3_12 · Cited by 3 · see citing works
Self-citationZhang, K., Fei, C., Xie, B., Wang, Y., Gong, Z., Xie, C., Nguyen, T. M. T., Yao, Y., & Miao, K. (2019) · Applied Sciences · doi:10.3390/app9153010 · Cited by 3 · see citing works
- Authors
- Hanheide, M., Göbelbecker, M., Horn, G. S., Pronobis, A., Sjöö, K., Aydemir, A., Jensfelt, P., Gretton, C., Dearden, R., Janicek, M., Zender, H., Kruijff, G.-J., Hawes, N., & Wyatt, J. L.
- Corresponding author
- Hanheide, Marc
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2017-06
- Volume
- 247
- Pages
- 119-150
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W2149280200
- Cited by
- 145
- References
- 68
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 14 · 2023: 10 · 2022: 12 · 2021: 18 · 2020: 19 · 2019: 24 · 2018: 12 · 2017: 16 · 2016: 7 · 2015: 1
- FWCI
- 11.77
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Artificial Intelligence (publishedVersion)
- Lincoln Repository (University of Lincoln) (acceptedVersion)
- ANU Open Research (Australian National University) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by-nc-nd)
- Funders
- Seventh Framework Programme (215181, 600623)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Keywords
- robot task planning, uncertainty, incomplete information, open world, assumptions, knowledge layer, commonsense knowledge, diagnostic knowledge, belief representation, mobile robots, object search, knowledge verification
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review