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P. Allen

11 papers hereh-index 6213.3k citations215 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author10

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.RO11
same name
  • P. Allen — 13 papers, h 12
  • P. Allen — 5 papers, h 7
  • P. Allen — 3 papers, h 8
  • P. Allen — 2 papers, h 27
  • P. Allen — 2 papers, h 5
  • P. Allen — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162023
most citedMAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning

10 citations · 10 across the 4 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.RO2019★ 10 cited

MAT: Multi-Fingered Adaptive Tactile Grasping via Deep Reinforcement Learning

Bohan Wu, Iretiayo Akinola, Jacob Varley +1

Vision-based grasping systems typically adopt an open-loop execution of a planned grasp. This policy can fail due to many reasons, including ubiquitous calibration error. Recovery…

cs.RO2019

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…

cs.RO2019

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…

cs.RO2019

Pixel-Attentive Policy Gradient for Multi-Fingered Grasping in Cluttered Scenes

Bohan Wu, Iretiayo Akinola, Peter K. Allen

Recent advances in on-policy reinforcement learning (RL) methods enabled learning agents in virtual environments to master complex tasks with high-dimensional and continuous observ…

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