3 citations · 4 across the 3 of their papers we have counts for
6 papers
Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation
Karol Arndt, Oliver Struckmeier, Ville Kyrki
Domain adaptation is a common problem in robotics, with applications such as transferring policies from simulation to real world and lifelong learning. Performing such adaptation,…
Autoencoding Slow Representations for Semi-supervised Data Efficient Regression
Oliver Struckmeier, Kshitij Tiwari, Ville Kyrki
The slowness principle is a concept inspired by the visual cortex of the brain. It postulates that the underlying generative factors of a quickly varying sensory signal change on a…
MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations
Oliver Struckmeier, Kshitij Tiwari, Shirin Dora +4
Extracting and binding salient information from different sensory modalities to determine common features in the environment is a significant challenge in robotics. Here we present…
ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments
Oliver Struckmeier, Kshitij Tiwari, Mohammed Salman +2
RatSLAM is a rat hippocampus-inspired visual Simultaneous Localization and Mapping (SLAM) framework capable of generating semi-metric topological representations of indoor and outd…
LeagueAI: Improving object detector performance and flexibility through automatically generated training data and domain randomization
Oliver Struckmeier
In this technical report I present my method for automatic synthetic dataset generation for object detection and demonstrate it on the video game League of Legends. This report fur…
ViTa-SLAM: Biologically-Inspired Visuo-Tactile SLAM
Oliver Struckmeier, Kshitij Tiwari, Martin J. Pearson +1
In this work, we propose a novel, bio-inspired multi-sensory SLAM approach called ViTa-SLAM. Compared to other multisensory SLAM variants, this approach allows for a seamless multi…