7 citations · 8 across the 5 of their papers we have counts for
6 papers
Multiple View Performers for Shape Completion
David Watkins, Peter Allen, Krzysztof Choromanski +2
We propose the Multiple View Performer (MVP) - a new architecture for 3D shape completion from a series of temporally sequential views. MVP accomplishes this task by using linear-a…
Mobile Manipulation Leveraging Multiple Views
David Watkins, Peter K Allen, Henrique Maia +4
While both navigation and manipulation are challenging topics in isolation, many tasks require the ability to both navigate and manipulate in concert. To this end, we propose a mob…
Accelerated Robot Learning via Human Brain Signals
Iretiayo Akinola, Zizhao Wang, Junyao Shi +6
In reinforcement learning (RL), sparse rewards are a natural way to specify the task to be learned. However, most RL algorithms struggle to learn in this setting since the learning…
Learning Your Way Without Map or Compass: Panoramic Target Driven Visual Navigation
David Watkins-Valls, Jingxi Xu, Nicholas Waytowich +1
We present a robot navigation system that uses an imitation learning framework to successfully navigate in complex environments. Our framework takes a pre-built 3D scan of a real e…
Human Robot Interface for Assistive Grasping
David Watkins, Chaiwen Chou, Caroline Weinberg +6
This work describes a new human-in-the-loop (HitL) assistive grasping system for individuals with varying levels of physical capabilities. We investigated the feasibility of using…
Multi-Modal Geometric Learning for Grasping and Manipulation
David Watkins, Jacob Varley, Peter Allen
This work provides an architecture that incorporates depth and tactile information to create rich and accurate 3D models useful for robotic manipulation tasks. This is accomplished…