33 citations · 118 across the 10 of their papers we have counts for
12 papers · 1 filter
Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation
Chia-Man Hung, Shaohong Zhong, Walter Goodwin +4
We present a novel approach to path planning for robotic manipulators, in which paths are produced via iterative optimisation in the latent space of a generative model of robot pos…
Fast-MbyM: Leveraging Translational Invariance of the Fourier Transform for Efficient and Accurate Radar Odometry
Robert Weston, Matthew Gadd, Daniele De Martini +2
Masking By Moving (MByM), provides robust and accurate radar odometry measurements through an exhaustive correlative search across discretised pose candidates. However, this dense…
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Nicholas Roy, Ingmar Posner, Tim Barfoot +17
Machine learning has long since become a keystone technology, accelerating science and applications in a broad range of domains. Consequently, the notion of applying learning metho…
APEX: Unsupervised, Object-Centric Scene Segmentation and Tracking for Robot Manipulation
Yizhe Wu, Oiwi Parker Jones, Martin Engelcke +1
Recent advances in unsupervised learning for object detection, segmentation, and tracking hold significant promise for applications in robotics. A common approach is to frame these…
Introspective Visuomotor Control: Exploiting Uncertainty in Deep Visuomotor Control for Failure Recovery
Chia-Man Hung, Li Sun, Yizhe Wu +2
End-to-end visuomotor control is emerging as a compelling solution for robot manipulation tasks. However, imitation learning-based visuomotor control approaches tend to suffer from…
There and Back Again: Learning to Simulate Radar Data for Real-World Applications
Rob Weston, Oiwi Parker Jones, Ingmar Posner
Simulating realistic radar data has the potential to significantly accelerate the development of data-driven approaches to radar processing. However, it is fraught with difficulty…