Showing 97 publications by Ingmar Posner
Reaching through latent space: From joint statistics to path planning in manipulation
Hung C-M, Zhong S, Goodwin W, Parker Jones O, Engelcke M et al. (2022), IEEE Robotics and Automation Letters
BibTeX
@article{reachingthrough-2022/2,
title={Reaching through latent space: From joint statistics to path planning in manipulation},
author={Hung C-M, Zhong S, Goodwin W, Parker Jones O, Engelcke M et al.},
journal={IEEE Robotics and Automation Letters},
publisher={Institute of Electrical and Electronics Engineers},
year = "2022"
}
Universal Approximation of Functions on Sets
Wagstaff E, Fuchs FB, Engelcke M, Osborne MA & Posner I (2022), Journal of Machine Learning Research, 23
BibTeX
@article{universalapprox-2022/1,
title={Universal Approximation of Functions on Sets},
author={Wagstaff E, Fuchs FB, Engelcke M, Osborne MA & Posner I},
journal={Journal of Machine Learning Research},
volume={23},
year = "2022"
}
Goal-conditioned end-to-end visuomotor control for versatile skill primitives
Groth O, Hung C, Vedaldi A & Posner I (2021), 2021 IEEE International Conference on Robotics and Automation (ICRA), 1319-1325
There and Back Again: Learning to Simulate Radar Data for Real-World Applications
Weston R, Jones OP & Posner I (2021), 2021 IEEE International Conference on Robotics and Automation (ICRA)
Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery
Hung C-M, Sun L, Wu Y, Havoutis I & Posner I (2021), 2021 IEEE International Conference on Robotics and Automation (ICRA)
BibTeX
@inproceedings{introspectivevi-2021/5,
title={Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery},
author={Hung C-M, Sun L, Wu Y, Havoutis I & Posner I},
booktitle={2021 IEEE International Conference on Robotics and Automation (ICRA)},
year = "2021"
}
First steps: latent-space control with semantic constraints for quadruped locomotion
Mitchell A, Engelcke M, Parker Jones O, Surovik D, Havoutis I et al. (2021), Proceedings of the IEEE International Workshop on Intelligent Robots and Systems (IROS), 5343-5350
APEX: Unsupervised, Object-Centric Scene Segmentation and Tracking for Robot Manipulation
Wu Y, Jones OP, Engelcke M & Posner I (2021), IEEE International Conference on Intelligent Robots and Systems, 3375-3382
E(n) Equivariant Normalizing Flows
Satorras VG, Hoogeboom E, Fuchs FB, Posner I & Welling M (2021), Advances in Neural Information Processing Systems, 6, 4181-4192
BibTeX
@inproceedings{enequivariantno-2021/1,
title={E(n) Equivariant Normalizing Flows},
author={Satorras VG, Hoogeboom E, Fuchs FB, Posner I & Welling M},
pages={4181-4192},
year = "2021"
}
Iterative SE(3)-Transformers
Fuchs FB, Wagstaff E, Dauparas J & Posner I (2021), GEOMETRIC SCIENCE OF INFORMATION (GSI 2021), 12829, 585-595
RELATE: physically plausible multi-object scene synthesis using structured latent spaces
Ehrhardt S, Groth O, Monszpart A, Engelcke M, Posner H et al. (2020), NIPS Proceedings, 33
BibTeX
@inproceedings{relatephysicall-2020/12,
title={RELATE: physically plausible multi-object scene synthesis using structured latent spaces},
author={Ehrhardt S, Groth O, Monszpart A, Engelcke M, Posner H et al.},
booktitle={NeurIPS 2020},
year = "2020"
}
Attention-privileged reinforcement learning
Salter S, Rao D, Wulfmeier M, Hadsell R & Posner H (2020), Proceedings of the Conference on Robot Learning 2020(2020)
BibTeX
@inproceedings{attentionprivil-2020/11,
title={Attention-privileged reinforcement learning},
author={Salter S, Rao D, Wulfmeier M, Hadsell R & Posner H},
booktitle={Conference of Robotic Learning},
year = "2020"
}
Under the radar: learning to predict robust keypoints for odometry estimation and metric localisation in radar
Barnes D & Posner H (2020), Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), 9484-9490
BibTeX
@inproceedings{undertheradarle-2020/9,
title={Under the radar: learning to predict robust keypoints for odometry estimation and metric localisation in radar},
author={Barnes D & Posner H},
booktitle={International Conference on Robotics and Automation 2020},
pages={9484-9490},
year = "2020"
}
Reconstruction bottlenecks in object-centric generative models
Engelcke M, Posner H & Parker Jones O (2020)
BibTeX
@inproceedings{reconstructionb-2020/7,
title={Reconstruction bottlenecks in object-centric generative models},
author={Engelcke M, Posner H & Parker Jones O},
booktitle={Workshop on Object-Oriented Learning at ICML 2020},
year = "2020"
}
Learning affordances in object-centric generative models
Wu Y, Kasewa S, Groth O, Salter S, Sun L et al. (2020)
BibTeX
@inproceedings{learningafforda-2020/7,
title={Learning affordances in object-centric generative models},
author={Wu Y, Kasewa S, Groth O, Salter S, Sun L et al.},
booktitle={Workshop on Object-Oriented Learning at ICML 2020},
year = "2020"
}
Robots thinking fast and slow: on dual process theory and metacognition in embodied AI
Posner H (2020)
BibTeX
@inproceedings{robotsthinkingf-2020/6,
title={Robots thinking fast and slow: on dual process theory and metacognition in embodied AI},
author={Posner H},
booktitle={RSS Workshop on Robotics Retrospectives},
year = "2020"
}
GENESIS: Generative Scene Inference and Sampling of Object-Centric Latent Representations
Engelcke M, Kosiorek A, Parker Jones O & Posner H (2020), Proceedings of the ICLR 2020
BibTeX
@inproceedings{genesisgenerati-2020/3,
title={GENESIS: Generative Scene Inference and Sampling of Object-Centric Latent Representations},
author={Engelcke M, Kosiorek A, Parker Jones O & Posner H},
booktitle={International Conference on Learning Representations 2020 (ICLR)},
year = "2020"
}
Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments
Sun L, Adolfsson D, Magnusson M, Andreasson H, Posner I et al. (2020), 2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 4386-4392
BibTeX
@inproceedings{localisingfaste-2020/,
title={Localising Faster: Efficient and precise lidar-based robot localisation in large-scale environments},
author={Sun L, Adolfsson D, Magnusson M, Andreasson H, Posner I et al.},
pages={4386-4392},
year = "2020"
}
Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information
POSNER H, Barnes D & Weston R (2019), arXiv:1909.03752v3
BibTeX
@article{maskingbymoving-2019/9,
title={Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information},
author={POSNER H, Barnes D & Weston R},
journal={arXiv:1909.03752v3},
year = "2019"
}
Scrutinizing and de-biasing intuitive physics with neural stethoscopes
Fuchs FB, Groth O, Kosiorek AR, Bewley A, Wulfmeier M et al. (2019), British Machine Vision Conference (BMVC), 2019
BibTeX
@inproceedings{scrutinizingand-2019/9,
title={Scrutinizing and de-biasing intuitive physics with neural stethoscopes},
author={Fuchs FB, Groth O, Kosiorek AR, Bewley A, Wulfmeier M et al.},
year = "2019"
}
The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset
Posner H, Newman P, Murcutt P, Barnes D & Gadd M (2019), arXiv Preprint arXiv: 1909.01300,2019
BibTeX
@inproceedings{theoxfordradarr-2019/9,
title={The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset},
author={Posner H, Newman P, Murcutt P, Barnes D & Gadd M},
year = "2019"
}
Probably unknown: Deep inverse sensor modelling radar
Weston R, Cen S, Newman P & Posner H (2019), International Conference on Robotics and Automation 2019 (ICRA 2019), 5446-5452
END-TO-END RECURRENT MULTI-OBJECT TRACKING AND TRAJECTORY PREDICTION WITH RELATIONAL REASONING
Posner H, Fuchs F, Kosiorek A, Sun L & Parker Jones O (2019), arXiv:1907.12887v3
BibTeX
@article{endtoendrecurre-2019/7,
title={END-TO-END RECURRENT MULTI-OBJECT TRACKING AND TRAJECTORY PREDICTION WITH RELATIONAL REASONING},
author={Posner H, Fuchs F, Kosiorek A, Sun L & Parker Jones O},
journal={arXiv:1907.12887v3},
year = "2019"
}
GENESIS: Generative Scene Inference and Sampling of Object-Centric Latent Representations
POSNER H, PARKER JONES OP, Engelcke M & Kosiorek A (2019), arXiv:1907.13052v2
BibTeX
@article{genesisgenerati-2019/7,
title={GENESIS: Generative Scene Inference and Sampling of Object-Centric Latent Representations},
author={POSNER H, PARKER JONES OP, Engelcke M & Kosiorek A},
journal={arXiv:1907.13052v2},
year = "2019"
}
On the limitations of representing functions on sets
Wagstaff E, Fuchs FB, Engelcke M, Posner I & Osborne MA (2019), Proceedings of Machine Learning Research, 97, 6487-6494
BibTeX
@inproceedings{onthelimitation-2019/6,
title={On the limitations of representing functions on sets},
author={Wagstaff E, Fuchs FB, Engelcke M, Posner I & Osborne MA},
pages={6487-6494},
year = "2019"
}
Long-term driving behaviour modelling for driver identification
Marchegiani L & Posner HI (2018), 21st IEEE International Conference on Intelligent Transportation Systems (ITSC 2018)
Driven to distraction: Self-supervised distractor learning for robust monocular visual odometry in urban environments
Barnes D, Maddern W, Pascoe G & Posner HI (2018), International Conference on Robotics and Automation (ICRA 2018)
Hierarchical attentive recurrent tracking
Kosiorek AR, Bewley A & Posner H (2018), 30th Neural Information Processing Systems (NIPS 2017)
BibTeX
@inproceedings{hierarchicalatt-2018/7,
title={Hierarchical attentive recurrent tracking},
author={Kosiorek AR, Bewley A & Posner H},
year = "2018"
}
TACO: Learning task decomposition via temporal alignment for control
Shiarlis K, Wulfmeier M, Salter S, Whiteson SA & Posner HI (2018), International Conference on Machine Learning
BibTeX
@inproceedings{tacolearningtas-2018/7,
title={TACO: Learning task decomposition via temporal alignment for control},
author={Shiarlis K, Wulfmeier M, Salter S, Whiteson SA & Posner HI},
year = "2018"
}
Off the beaten track: predicting localisation performance in visual teach and repeat
Dequaire J, Tong C, Churchill W & Posner I (2018), IEEE International Conference on Robotics and Automation (ICRA), 795-800
BibTeX
@inproceedings{offthebeatentra-2018/6,
title={Off the beaten track: predicting localisation performance in visual teach and repeat},
author={Dequaire J, Tong C, Churchill W & Posner I},
booktitle={Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.},
pages={795-800},
year = "2018"
}
Resource-performance trade-off analysis for mobile robots
Lahijanian M, Svorenova M, Morye AA, Yeomans B, Rao D et al. (2018), IEEE Robotics and Automation Letters, 3(3), 1840-1847
TACO: Learning Task Decomposition via Temporal Alignment for Control.
Shiarlis K, Wulfmeier M, Salter S, Whiteson S & Posner I (2018), CoRR
BibTeX
@article{tacolearningtas-2018/1,
title={TACO: Learning Task Decomposition via Temporal Alignment for Control.},
author={Shiarlis K, Wulfmeier M, Salter S, Whiteson S & Posner I},
journal={CoRR},
year = "2018"
}
ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking
Groth O, Fuchs FB, Posner I & Vedaldi A (2018), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11205 LNCS, 724-739
BibTeX
@inproceedings{shapestackslear-2018/1,
title={ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking},
author={Groth O, Fuchs FB, Posner I & Vedaldi A},
booktitle={Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
pages={724-739},
year = "2018"
}
Dropout distillation for efficiently estimating model confidence
Gurau C, Bewley A & Posner HI (2018), arXiv
BibTeX
@article{dropoutdistilla-2018/1,
title={Dropout distillation for efficiently estimating model confidence},
author={Gurau C, Bewley A & Posner HI},
journal={arXiv},
year = "2018"
}
Neural stethoscopes: Unifying analytic, auxiliary and adversarial network probing
Fuchs FB, Groth O, Kosiorek AR, Bewley A, Wulfmeier M et al. (2018), arXiv
BibTeX
@article{neuralstethosco-2018/1,
title={Neural stethoscopes: Unifying analytic, auxiliary and adversarial network probing},
author={Fuchs FB, Groth O, Kosiorek AR, Bewley A, Wulfmeier M et al.},
journal={arXiv},
year = "2018"
}
Incremental Adversarial Domain Adaptation for Continually Changing Environments
Wulfmeier M, Bewley A, Posner I & IEEE (2018), 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 4489-4495
BibTeX
@inproceedings{incrementaladve-2018/,
title={Incremental Adversarial Domain Adaptation for Continually Changing Environments},
author={Wulfmeier M, Bewley A, Posner I & IEEE },
booktitle={2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)},
pages={4489-4495},
year = "2018"
}
What makes a place? Building bespoke place dependent object detectors
Hawke J, Bewley A & Posner HI (2017), IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
Addressing appearance change in outdoor robotics with adversarial domain adaptation
Wulfeier M, Bewley A & Posner HI (2017), IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
Bayesian Delay Embeddings for Dynamical Systems
Dhir N, Kosiorek A & Posner H (2017), 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.
BibTeX
@inproceedings{bayesiandelayem-2017/11,
title={Bayesian Delay Embeddings for Dynamical Systems},
author={Dhir N, Kosiorek A & Posner H},
year = "2017"
}
Mutual alignment transfer learning
Wulfmeier MR, Posner HI & Abbeel P (2017), 1st Conference on Robot Learning (CoRL 2017)
BibTeX
@inproceedings{mutualalignment-2017/10,
title={Mutual alignment transfer learning},
author={Wulfmeier MR, Posner HI & Abbeel P},
year = "2017"
}
Learn from experience: probabilistic prediction of perception performance to avoid failure
Gurău C, Rao D, Tong CH & Posner I (2017), The International Journal of Robotics Research, 027836491773060-027836491773060
BibTeX
@article{learnfromexperi-2017/10,
title={Learn from experience: probabilistic prediction of perception performance to avoid failure},
author={Gurău C, Rao D, Tong CH & Posner I},
journal={The International Journal of Robotics Research},
pages={027836491773060-027836491773060},
year = "2017"
}
Large-scale cost function learning for path planning using deep inverse reinforcement learning
Wulfmeier M, Rao D, Wang DZ, Ondruska P & Posner I (2017), INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 36(10), 1073-1087
BibTeX
@article{largescalecostf-2017/9,
title={Large-scale cost function learning for path planning using deep inverse reinforcement learning},
author={Wulfmeier M, Rao D, Wang DZ, Ondruska P & Posner I},
journal={INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH},
volume={36},
pages={1073-1087},
year = "2017"
}
Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks
Engelcke M, Rao D, Wang DZ, Tong CH & Posner I (2017), Proceedings - IEEE International Conference on Robotics and Automation, 1355-1361
BibTeX
@inproceedings{votedeepfastobj-2017/7,
title={Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks},
author={Engelcke M, Rao D, Wang DZ, Tong CH & Posner I},
booktitle={Conference on Robotics and Automation (ICRA)},
pages={1355-1361},
year = "2017"
}
Leveraging the urban soundscape: Auditory perception for smart vehicles
Marchegiani L & Posner I (2017), Proceedings - IEEE International Conference on Robotics and Automation, 6547-6554
Find your own way: Weakly-supervised segmentation of path proposals for urban autonomy
Barnes D, Maddern W & Posner I (2017), Proceedings - IEEE International Conference on Robotics and Automation, 203-210
Deep tracking in the wild: End-to-end tracking using recurrent neural networks
Dequaire J, OndrúÅ¡ka P, Rao D, Wang D & Posner I (2017), The International Journal of Robotics Research, 027836491771054-027836491771054
BibTeX
@article{deeptrackingint-2017/6,
title={Deep tracking in the wild: End-to-end tracking using recurrent neural networks},
author={Dequaire J, OndrúÅ¡ka P, Rao D, Wang D & Posner I},
journal={The International Journal of Robotics Research},
pages={027836491771054-027836491771054},
year = "2017"
}
Fit for purpose? Predicting perception performance based on past experience
Gurau C, Tong H & Posner H (2017), International Symposium on Experimental Robotics (ISER)
Enabling intelligent energy management for robots using publicly available maps
Bartlett O, Gurau C, Marchegiani L & Posner I (2016), IROS 2016: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2224-2229
Automated valet parking and charging for e-mobility
Schwesinger U, Bürki M, Timpner J, Rottmann S, Wolf L et al. (2016), 2016 IEEE Intelligent Vehicles Symposium (IV), 157-164
Introspective classification for robot perception
Grimmett H, Triebel R, Paul R & Posner I (2016), INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 35(7), 743-762
End-to-end tracking and semantic segmentation using recurrent neural networks
Ondruska P, Dequaire J, Zen Wang D & Posner HI (2016), Robotics Science and Systems 2016, Workshop on Limits and Potentials of Deep Learning in Robotics
BibTeX
@inproceedings{endtoendtrackin-2016/6,
title={End-to-end tracking and semantic segmentation using recurrent neural networks},
author={Ondruska P, Dequaire J, Zen Wang D & Posner HI},
year = "2016"
}
Erratum: Introspective Classification for Robot Perception (International Journal of Robotics Research (2016) 35 (743-762) DOI: 10.1177/0278364915587924)
Grimmett H, Triebel RA, Paul R & Posner I (2016), International Journal of Robotics Research, 35(7), 763-766
BibTeX
@article{erratumintrospe-2016/6,
title={Erratum: Introspective Classification for Robot Perception (International Journal of Robotics Research (2016) 35 (743-762) DOI: 10.1177/0278364915587924)},
author={Grimmett H, Triebel RA, Paul R & Posner I},
journal={International Journal of Robotics Research},
volume={35},
pages={763-766},
year = "2016"
}
Choosing a time and place for calibration of lidar-camera systems
Scott T, Morye AA, Pinies P, Paz LM, Posner I et al. (2016), Proceedings - IEEE International Conference on Robotics and Automation, 2016-June, 4349-4356
Wrong Today, Right Tomorrow: Experience-Based Classification for Robot Perception
Hawke J, Gurau C, Tong CH & Posner I (2016), FIELD AND SERVICE ROBOTICS: RESULTS OF THE 10TH INTERNATIONAL CONFERENCE, 113, 173-186
Driven Learning for Driving: How Introspection Improves Semantic Mapping
Triebel R, Grimmett H, Paul R & Posner I (2016), ROBOTICS RESEARCH, ISRR, 114, 449-465
Automated Valet Parking and Charging for e-Mobility
Schwesinger U, Buerki M, Timpner J, Rottmann S, Wolf L et al. (2016), 2016 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 157-164
BibTeX
@inproceedings{automatedvaletp-2016/,
title={Automated Valet Parking and Charging for e-Mobility},
author={Schwesinger U, Buerki M, Timpner J, Rottmann S, Wolf L et al.},
pages={157-164},
year = "2016"
}
Watch This: Scalable Cost-Function Learning for Path Planning in Urban Environments
Wulfmeier M, Wang DZ, Posner I & IEEE (2016), 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), 2089-2095
BibTeX
@inproceedings{watchthisscalab-2016/,
title={Watch This: Scalable Cost-Function Learning for Path Planning in Urban Environments},
author={Wulfmeier M, Wang DZ, Posner I & IEEE },
pages={2089-2095},
year = "2016"
}
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Ondruska P, Posner I & AAAI (2016), THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 3361-3367
BibTeX
@inproceedings{deeptrackingsee-2016/,
title={Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks},
author={Ondruska P, Posner I & AAAI },
pages={3361-3367},
year = "2016"
}
A New Approach to Model-Free Tracking with 2D Lidar
Wang DZ, Posner I & Newman P (2016), ROBOTICS RESEARCH, ISRR, 114, 557-573
Exploiting known unknowns: Scene induced cross-calibration of lidar-stereo systems
Scott T, Morye AA, Piniés P, Paz LM, Posner I et al. (2015), IEEE International Conference on Intelligent Robots and Systems, 2015-December, 3647-3653
Reading the Road: Road Marking Classification and Interpretation
Mathibela B, Newman P & Posner I (2015), IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 16(4), 2072-2081
Model-free detection and tracking of dynamic objects with 2D lidar
Wang DZ, Posner I & Newman P (2015), INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 34(7), 1039-1063
Scheduled Perception for Energy-Efficient Path Following
Ondruska P, Gurau C, Marchegiani L, Tong CH, Posner I et al. (2015), 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 4799-4806
BibTeX
@inproceedings{scheduledpercep-2015/,
title={Scheduled Perception for Energy-Efficient Path Following},
author={Ondruska P, Gurau C, Marchegiani L, Tong CH, Posner I et al.},
pages={4799-4806},
year = "2015"
}
Learning to Assess Terrain from Human Demonstration Using an Introspective Gaussian-Process Classifier
Berczi L-P, Posner I, Barfoot TD & IEEE (2015), 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 3178-3185
BibTeX
@inproceedings{learningtoasses-2015/,
title={Learning to Assess Terrain from Human Demonstration Using an Introspective Gaussian-Process Classifier},
author={Berczi L-P, Posner I, Barfoot TD & IEEE },
pages={3178-3185},
year = "2015"
}
Exploiting 3D Semantic Scene Priors for Online Traffic Light Interpretation
Barnes D, Maddern W, Posner I & IEEE (2015), 2015 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 573-578
BibTeX
@inproceedings{exploitingdsema-2015/,
title={Exploiting 3D Semantic Scene Priors for Online Traffic Light Interpretation},
author={Barnes D, Maddern W, Posner I & IEEE },
pages={573-578},
year = "2015"
}
Voting for Voting in Online Point Cloud Object Detection
Wang DL & Posner I (2015), ROBOTICS: SCIENCE AND SYSTEMS XI
BibTeX
@inproceedings{votingforvoting-2015/,
title={Voting for Voting in Online Point Cloud Object Detection},
author={Wang DL & Posner I},
year = "2015"
}
From Dusk till Dawn: Localisation at Night using Artificial Light Sources
Nelson P, Churchill W, Posner I, Newman P & IEEE (2015), 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 5245-5252
BibTeX
@inproceedings{fromdusktilldaw-2015/,
title={From Dusk till Dawn: Localisation at Night using Artificial Light Sources},
author={Nelson P, Churchill W, Posner I, Newman P & IEEE },
pages={5245-5252},
year = "2015"
}
Know Your Limits: Embedding Localiser Performance Models in Teach and Repeat Maps
Churchill W, Tong CH, Gurau C, Posner I, Newman P et al. (2015), 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 4238-4244
BibTeX
@inproceedings{knowyourlimitse-2015/,
title={Know Your Limits: Embedding Localiser Performance Models in Teach and Repeat Maps},
author={Churchill W, Tong CH, Gurau C, Posner I, Newman P et al.},
pages={4238-4244},
year = "2015"
}
Integrating Metric and Semantic Maps for Vision-Only Automated Parking
Grimmett H, Buerki M, Paz L, Pinies P, Furgale P et al. (2015), 2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2159-2166
BibTeX
@inproceedings{integratingmetr-2015/,
title={Integrating Metric and Semantic Maps for Vision-Only Automated Parking},
author={Grimmett H, Buerki M, Paz L, Pinies P, Furgale P et al.},
pages={2159-2166},
year = "2015"
}
Probabilistic Attainability Maps: Efficiently Predicting Driver-Specific Electric Vehicle Range
Ondruska P, Posner I & IEEE (2014), 2014 IEEE INTELLIGENT VEHICLES SYMPOSIUM PROCEEDINGS, 1169-1174
BibTeX
@inproceedings{probabilisticat-2014/,
title={Probabilistic Attainability Maps: Efficiently Predicting Driver-Specific Electric Vehicle Range},
author={Ondruska P, Posner I & IEEE },
pages={1169-1174},
year = "2014"
}
The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range
Ondruska P, Posner I & Intelligence AAA (2014), TWENTY-FOURTH INTERNATIONAL CONFERENCE ON AUTOMATED PLANNING AND SCHEDULING, 413-420
BibTeX
@inproceedings{theroutenottake-2014/,
title={The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range},
author={Ondruska P, Posner I & Intelligence AAA},
pages={413-420},
year = "2014"
}
Toward automated driving in cities using close-to-market sensors: An overview of the V-Charge Project
Furgale P, Schwesinger U, Rufli M, Derendarz W, Grimmett H et al. (2013), IEEE Intelligent Vehicles Symposium, Proceedings, 809-816
A roadwork scene signature based on the opponent colour model
Mathibela B, Posner I & Newman P (2013), IEEE International Conference on Intelligent Robots and Systems, 4394-4400
Knowing when we don't know: Introspective classification for mission-critical decision making
Grimmett H, Paul R, Triebel R & Posner I (2013), Proceedings - IEEE International Conference on Robotics and Automation, 4531-4538
Can priors be trusted? Learning to anticipate roadworks
Mathibela B, Osborne MA, Posner I & Newman P (2012), IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 927-932
What could move? Finding cars, pedestrians and bicyclists in 3D laser data
Wang DZ, Posner I & Newman P (2012), Proceedings - IEEE International Conference on Robotics and Automation, 4038-4044
Modelling Observation Correlations for Active Exploration and Robust Object Detection
Velez J, Hemann G, Huang AS, Posner I & Roy N (2012), JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 44, 423-453
Active exploration for robust object detection
Velez J, Hemann G, Huang AS, Posner I & Roy N (2011), IJCAI International Joint Conference on Artificial Intelligence, 2752-2757
Adaptive data compression for robot perception
Smith M, Posner I & Newman P (2011), IJCAI International Joint Conference on Artificial Intelligence, 2746-2751
Planning to perceive: Exploiting mobility for robust object detection
Velez J, Hemann G, Huang AS, Posner I & Roy N (2011), ICAPS 2011 - Proceedings of the 21st International Conference on Automated Planning and Scheduling, 266-273
BibTeX
@article{planningtoperce-2011/10,
title={Planning to perceive: Exploiting mobility for robust object detection},
author={Velez J, Hemann G, Huang AS, Posner I & Roy N},
journal={ICAPS 2011 - Proceedings of the 21st International Conference on Automated Planning and Scheduling},
pages={266-273},
year = "2011"
}
Adaptive compression for 3D laser data
Smith M, Posner I & Newman P (2011), International Journal of Robotics Research, 30(7), 914-935
Efficient Non-parametric Surface Representations Using Active Sampling for Push Broom Laser Data
Smith M, Posner I & Newman P (2011), ROBOTICS: SCIENCE AND SYSTEMS VI, 209-216
BibTeX
@inproceedings{efficientnonpar-2011/,
title={Efficient Non-parametric Surface Representations Using Active Sampling for Push Broom Laser Data},
author={Smith M, Posner I & Newman P},
pages={209-216},
year = "2011"
}
Using text-spotting to query the world
Posner I, Corke P & Newman P (2010), IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings, 3181-3186
Describing, navigating and recognising urban spaces - Building an end-to-end SLAM system
Newman P, Chandran-Ramesh M, Cole D, Cummins M, Harrison A et al. (2010), Springer Tracts in Advanced Robotics, 66(STAR), 237-253
Navigating, recognizing and describing urban spaces with vision and lasers
Newman P, Sibley G, Smith M, Cummins M, Harrison A et al. (2009), International Journal of Robotics Research, 28(11-12), 1406-1433
A generative framework for fast urban labeling using spatial and temporal context
Posner I, Cummins M & Newman P (2009), Autonomous Robots, 26(2-3), 153-170
Online generation of scene descriptions in urban environments
Posner I, Schroeter D & Newman P (2008), Robotics and Autonomous Systems, 56(11), 901-914
Using scene similarity for place labelling
Posner I, Schroeter D & Newman PM (2008), Springer Tracts in Advanced Robotics, 39, 85-98
Describing composite urban workspaces
Posner I, Schroeter D & Newman P (2007), Proceedings - IEEE International Conference on Robotics and Automation, 4962-4968
Incorporating Human Domain Knowledge into Large Scale Cost Function Learning
Posner HI, Wulfmeier M & Rao D (0)
BibTeX
@inproceedings{incorporatinghu-/,
title={Incorporating Human Domain Knowledge into Large Scale Cost Function Learning},
author={Posner HI, Wulfmeier M & Rao D},
booktitle={Neural Information Processing Systems Conference}
}
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Kosiorek AR, Kim H, Posner I & Teh YEE (0)
BibTeX
@inproceedings{sequentialatten-/,
title={Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects},
author={Kosiorek AR, Kim H, Posner I & Teh YEE}
}
On the Limitations of Representing Functions on Sets
Posner H, Wagstaff E, Fuchs F, Engelcke M & Osborne M (0), arXiv preprint arXiv:1901.09006 2019
BibTeX
@article{onthelimitation-/,
title={On the Limitations of Representing Functions on Sets},
author={Posner H, Wagstaff E, Fuchs F, Engelcke M & Osborne M},
journal={arXiv preprint arXiv:1901.09006 2019}
}
Imagine That! Leveraging Emergent Affordances for Tool Synthesis in Reaching Tasks
Wu Y, Kasewa S, Groth O, Salter S, Sun L et al. (0), arXiv preprint arXiv:1909.13561, 2019.
BibTeX
@article{imaginethatleve-/,
title={Imagine That! Leveraging Emergent Affordances for Tool Synthesis in
Reaching Tasks},
author={Wu Y, Kasewa S, Groth O, Salter S, Sun L et al.},
journal={arXiv preprint arXiv:1909.13561, 2019.}
}
Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives
Posner H, Vedaldi A, Hung C & Groth O (0), ArXiv, 2020
BibTeX
@article{goalconditioned-/,
title={Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives},
author={Posner H, Vedaldi A, Hung C & Groth O},
journal={ArXiv, 2020}
}
GENESIS-V2: inferring unordered object representations without iterative refinement
Engelcke M, Parker Jones O & Posner I (0), Robotics
BibTeX
@inproceedings{genesisvinferri-/,
title={GENESIS-V2: inferring unordered object representations without iterative refinement},
author={Engelcke M, Parker Jones O & Posner I},
booktitle={Robotics Journal}
}
Resource-Performance Trade-off Analysis for Mobile Robot Design
Lahijanian M, Svorenova M, Morye AA, Yeomans B, Rao D et al. (0), arXiv
BibTeX
@article{resourceperform-/,
title={Resource-Performance Trade-off Analysis for Mobile Robot Design},
author={Lahijanian M, Svorenova M, Morye AA, Yeomans B, Rao D et al.},
journal={arXiv}
}
GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement
Posner H, Engelcke M & Parker Jones O (0), arXiv preprint: 2104.09958.
BibTeX
@article{genesisvinferri-/,
title={GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement},
author={Posner H, Engelcke M & Parker Jones O},
journal={arXiv preprint: 2104.09958.}
}