no code implementations • 13 Sep 2022 • David Watkins-Valls, Peter Allen, Krzysztof Choromanski, Jacob Varley, Nicholas Waytowich
We propose the Multiple View Performer (MVP) - a new architecture for 3D shape completion from a series of temporally sequential views.
no code implementations • 24 Mar 2021 • Iretiayo Akinola, Zizhao Wang, Peter Allen
We propose a vision-based reinforcement learning (RL) approach for closed-loop trajectory generation in an arm reaching problem.
no code implementations • 20 Sep 2019 • David Watkins-Valls, Jingxi Xu, Nicholas Waytowich, Peter Allen
We present a robot navigation system that uses an imitation learning framework to successfully navigate in complex environments.
no code implementations • 10 Sep 2019 • Bohan Wu, Iretiayo Akinola, Jacob Varley, Peter Allen
When this methodology is used to realize grasps from coarse initial positions provided by a vision-only planner, the system is made dramatically more robust to calibration errors in the camera-robot transform.
1 code implementation • 20 Mar 2018 • Jacob Varley, David Watkins-Valls, Peter Allen
At runtime, the network is provided a partial view of an object and tactile information is acquired to augment the captured depth information.
Robotics
no code implementations • 27 Sep 2016 • Jacob Varley, Chad DeChant, Adam Richardson, Joaquín Ruales, Peter Allen
At runtime, a 2. 5D pointcloud captured from a single point of view is fed into the CNN, which fills in the occluded regions of the scene, allowing grasps to be planned and executed on the completed object.
Robotics
no code implementations • 15 Jul 2016 • Yinxiao Li, Yan Wang, Yonghao Yue, Danfei Xu, Michael Case, Shih-Fu Chang, Eitan Grinspun, Peter Allen
A fully featured 3D model of the garment is constructed in real-time and volumetric features are then used to obtain the most similar model in the database to predict the object category and pose.
no code implementations • 13 Dec 2015 • Jiongxin Liu, Yinxiao Li, Peter Allen, Peter Belhumeur
Exemplar-based models have achieved great success on localizing the parts of semi-rigid objects.