14 citations · 17 across the 6 of their papers we have counts for
4 papers · 1 filter
Working Backwards: Learning to Place by Picking
Oliver Limoyo, Abhisek Konar, Trevor Ablett +3
We present placing via picking (PvP), a method to autonomously collect real-world demonstrations for a family of placing tasks in which objects must be manipulated to specific, con…
PEOPLEx: PEdestrian Opportunistic Positioning LEveraging IMU, UWB, BLE and WiFi
Pierre-Yves Lajoie, Bobak Hamed Baghi, Sachini Herath +3
This paper advances the field of pedestrian localization by introducing a unifying framework for opportunistic positioning based on nonlinear factor graph optimization. While many…
Generalizable Imitation Learning Through Pre-Trained Representations
Wei-Di Chang, Francois Hogan, Scott Fujimoto +2
In this paper, we leverage self-supervised vision transformer models and their emergent semantic abilities to improve the generalization abilities of imitation learning policies. W…
Multimodal and Force-Matched Imitation Learning with a See-Through Visuotactile Sensor
Trevor Ablett, Oliver Limoyo, Adam Sigal +5
Contact-rich tasks continue to present many challenges for robotic manipulation. In this work, we leverage a multimodal visuotactile sensor within the framework of imitation learni…