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Dr Jack Collins

Dr

Jack Collins PhD

Postdoctoral Research Fellow

COLLEGE: Kellogg College

Biography

Dr. Jack Collins is a Postdoctoral Researcher in the Applied AI Lab, a lab within the Oxford Robotics Institute. He is also a research member of Kellogg College. Jack received his Ph.D. degree in robotics from the Queensland University of Technology (QUT), Australia, in 2022, and his B.Eng. (Hons.) degree in mechatronic engineering from QUT in 2017.

During his academic career, Jack has collaborated with leading research institutions such as the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia and the Manufacturing Technology Centre (MTC) in the UK, as well as a number of other academic and industry partners. These collaborations have helped ground his research in real-world problems and applications.

Personal Website

Research Interests

 

Jack's research is at the intersection of machine learning and robotics, in particular, looking at modelling the world for agents, task planning for long-horizon tasks, and scene representation for agents. He aims to apply his work to real-world robots with the intention of enabling robots to interact and manipulate their environment, much like people can.

 

Research Groups

Related Academics

Publications

DreamUp3D: object-centric generative models for single-view 3D scene understanding and real-to-sim transfer

Wu Y, Sáez de Ocáriz Borde H, Collins J, Jones OP & Posner I (2024), IEEE Robotics and Automation Letters, 9(4), 3291-3298

BibTeX View PDF
@article{dreamupdobjectc-2024/2,
  title={DreamUp3D: object-centric generative models for single-view 3D scene understanding and real-to-sim transfer},
  author={Wu Y, Sáez de Ocáriz Borde H, Collins J, Jones OP & Posner I},
  journal={IEEE Robotics and Automation Letters},
  volume={9},
  pages={3291-3298},
  publisher={IEEE},
  year = "2024"
}

RAMP: a benchmark for evaluating robotic assembly manipulation and planning

Collins J, Robson M, Yamada J, Sridharan M, Janik K et al. (2023), IEEE Robotics and Automation Letters, 9(1), 9-16

BibTeX View PDF
@article{rampabenchmarkf-2023/11,
  title={RAMP: a benchmark for evaluating robotic assembly manipulation and planning},
  author={Collins J, Robson M, Yamada J, Sridharan M, Janik K et al.},
  journal={IEEE Robotics and Automation Letters},
  volume={9},
  pages={9-16},
  publisher={IEEE},
  year = "2023"
}

Leveraging scene embeddings for gradient-based motion planning in latent space

Yamada J, Hung CM, Collins J, Havoutis I & Posner I (2023), 2023 IEEE International Conference on Robotics and Automation (ICRA), 5674-5680

BibTeX View PDF
@inproceedings{leveragingscene-2023/7,
  title={Leveraging scene embeddings for gradient-based motion planning in latent space},
  author={Yamada J, Hung CM, Collins J, Havoutis I & Posner I},
  booktitle={2023 IEEE International Conference on Robotics and Automation (ICRA)},
  pages={5674-5680},
  year = "2023"
}

RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning

Collins J, Robson M, Yamada J, Sridharan M, Janik K et al. (2023)

BibTeX
@misc{rampabenchmarkf-2023/5,
  title={RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and
  Planning},
  author={Collins J, Robson M, Yamada J, Sridharan M, Janik K et al.},
  year = "2023"
}

Follow the Gradient: Crossing the Reality Gap using Differentiable Physics (RealityGrad)

Collins J, Brown R, Leitner J & Howard D (2021)

BibTeX
@misc{followthegradie-2021/9,
  title={Follow the Gradient: Crossing the Reality Gap using Differentiable
  Physics (RealityGrad)},
  author={Collins J, Brown R, Leitner J & Howard D},
  year = "2021"
}

A review of physics simulators for robotic applications

Collins J, Chand S, Vanderkop A & Howard D (2021), IEEE Access, 9, 51416-51431

BibTeX View PDF
@article{areviewofphysic-2021/1,
  title={A review of physics simulators for robotic applications},
  author={Collins J, Chand S, Vanderkop A & Howard D},
  journal={IEEE Access},
  volume={9},
  pages={51416-51431},
  year = "2021"
}

Traversing the Reality Gap via Simulator Tuning

Collins J, Brown R, Leitner J & Howard D (2020)

BibTeX
@misc{traversingthere-2020/3,
  title={Traversing the Reality Gap via Simulator Tuning},
  author={Collins J, Brown R, Leitner J & Howard D},
  year = "2020"
}

Benchmarking Simulated Robotic Manipulation through a Real World Dataset

Collins J, McVicar J, Wedlock D, Brown R, Howard D et al. (2019)

BibTeX
@misc{benchmarkingsim-2019/11,
  title={Benchmarking Simulated Robotic Manipulation through a Real World Dataset},
  author={Collins J, McVicar J, Wedlock D, Brown R, Howard D et al.},
  year = "2019"
}

Comparing Direct and Indirect Representations for Environment-Specific Robot Component Design

Collins J, Cottier B & Howard D (2019), 00, 2705-2712

BibTeX View PDF
@inproceedings{comparingdirect-2019/6,
  title={Comparing Direct and Indirect Representations for Environment-Specific Robot Component Design},
  author={Collins J, Cottier B & Howard D},
  booktitle={2019 IEEE Congress on Evolutionary Computation (CEC)},
  pages={2705-2712},
  year = "2019"
}

Quantifying the Reality Gap in Robotic Manipulation Tasks

Collins J, Howard D & Leitner J (2019), 00, 6706-6712

BibTeX View PDF
@inproceedings{quantifyingther-2019/5,
  title={Quantifying the Reality Gap in Robotic Manipulation Tasks},
  author={Collins J, Howard D & Leitner J},
  booktitle={2019 International Conference on Robotics and Automation (ICRA)},
  pages={6706-6712},
  year = "2019"
}
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