Research Output
Conference and Journal Publications (where * denotes equal contribution):
[RA-L 2024, accepted to appear] W. Zhi, H. Tang, T. Zhang, M. Johnson-Roberson. Teaching Periodic Stable Robot Motion Generation Via Sketch.
[RA-L 2024] W. Zhi, H. Tang, T. Zhang, M. Johnson-Roberson. Simultaneous Geometry and Pose Estimation of Grasped Objects via 3D Foundation Models.
[RA-L 2024] W. Zhi, H. Tang, T. Zhang, M. Johnson-Roberson. Unifying Representation and Calibration with 3D Foundation Models.
[RA-L 2024, accepted to appear] T. Zhang, W. Zhi, et al. RecGS: Removing Water Caustic with Recurrent Gaussian Splatting.
[IROS 2024] Q. Sun*, W. Zhi*, T. Zhang, M. Johnson-Roberson. Diagrammatic Instructions to Specify Spatial Objectives and Constraints with Applications to Mobile Base Placement.
[IROS 2024] H. Wright, W. Zhi, M. Johnson-Roberson, T. Hermans. V-PRISM: Probabilistic Mapping of Unknown Tabletop Scenes.
[IROS 2024] T. Zhang, K. Huang, W. Zhi, M. Johnson-Roberson. DarkGS: Learning Neural Illumination and 3D Gaussians Relighting for Robotic Exploration in the Dark.
[IROS 2024] T. Lai, W.Zhi, T. Hermans, F. Ramos. Learning for Kinodynamic Tree Expansion.
[ICRA 2024] W. Zhi, T. Zhang, M. Johnson-Roberson. Instructing Robots by Sketching: Learning from Demonstration via Probabilistic Diagrammatic Teaching.
[ICRA 2024] H. Wang, W.Zhi, G. Batista, R. Chandra. Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning.
[ICRA 2023] W. Zhi, I. Akinola, K. Van Wyk, N. Ratliff, F. Ramos. Global and Reactive Motion Generation with Geometric Fabric Command Sequences.
[ICML 2022] W. Zhi, T. Lai, L. Ott, E. V. Bonilla, F. Ramos. Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks.
[L4DC 2022, Best Paper Award] W. Zhi, T. Lai, L. Ott, F. Ramos. Diffeomorphic Transforms for Generalised Imitation Learning.
[CORL 2021] T. Lai, W. Zhi, T. Hermans, F. Ramos. Parallelised Diffeomorphic Sampling-based Motion Planning.
[IROS 2021] W. Zhi, L. Ott, F. Ramos. Probabilistic Trajectory Prediction with Structural Constraints.
[IROS 2021] W. Zhi *, T. Lai *, L. Ott, F. Ramos. Trajectory Generation in New Environments from Past Experiences.
[ICRA 2021] W. Zhi, T. Lai, L. Ott, F. Ramos. Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements.
[CORL 2019] W. Zhi, L. Ott, F. Ramos Kernel trajectory maps for multi-modal probabilistic motion prediction.
[RA-L + IROS 2019] W. Zhi, R. Senanyake, L. Ott, F. Ramos. Spatiotemporal learning of directional uncertainty in urban environments with kernel recurrent mixture density networks.
[ICRA 2019] W. Zhi, R. Senanyake, L. Ott, F. Ramos. Continuous Occupancy Map Fusion with Fast Bayesian Hilbert Maps.
Conference and Journal Publications under review:
[ICRA 2025, under review] PhotoReg: Photometrically Registering 3D Gaussian Splatting Models. Z. Yuan, T. Zhang, M. Johnson-Roberson, W. Zhi.
[ICRA 2025, under review] SplaTraj: Camera Trajectory Generation with Semantic Gaussian Splatting. X. Liu, T. Zhang, M. Johnson-Roberson, W. Zhi.
[RA-L under review] Robust Bayesian Scene Reconstruction by Leveraging Retrieval-Augmented Priors. H. Wright, W. Zhi, M. Johnson-Roberson, T. Hermans.
[RA-L under review] ModCube: Modular, Self-Assembling Cubic Underwater Robot. J. Zheng, et al., W. Zhi, D. Fan.
[T-RO under review] Multi-query Robotic Manipulator Task Sequencing with Gromov-Hausdorff Approximations. F. Sukkar, J. Wakulicz, K. M. B. Lee, W. Zhi, R. Fitch.
I have also published work on machine learning for medical imaging, prior to my PhD, these include:
[DICTA 2017] Using convolutional neural networks and transfer learning for bone age classification. J. Zhou, Z. Li, W. Zhi, B. Liang, D. Moses, L., Dawes.
[ICONIP 2017] Using transfer learning with convolutional neural networks to diagnose breast cancer from histopathological images. W. Zhi, H.W.F Yeung, Z. Chen, S.M. Zandavi, Z. Lu, Y.Y. Chung.