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Author ORCID Identifier
N/A
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Computer Science
Year Degree Awarded
2018
Month Degree Awarded
September
First Advisor
Erik Learned-Miller
Second Advisor
Rod Grupen
Subject Categories
Artificial Intelligence and Robotics | Cognitive Neuroscience | Robotics
Abstract
In the book "On Intelligence", Hawkins states that intelligence should be measured by the capacity to memorize and predict patterns. I further suggest that the ability to predict action consequences based on perception and memory is essential for robots to demonstrate intelligent behaviors in unstructured environments. However, traditional approaches generally represent action and perception separately---as computer vision modules that recognize objects and as planners that execute actions based on labels and poses. I propose here a more integrated approach where action and perception are combined in a memory model, in which a sequence of actions can be planned based on predicted action outcomes. In this framework, hierarchical visual features based on convolutional neural networks are introduced to capture the essential affordances. These features in different hierarchies are associated with robot controllers of corresponding kinematic subchains to support manipulation. Through learning from demonstration, both actions and informative features in the memory model can be learned efficiently. As more demonstrations are recorded and more interactions are observed, the robot becomes more capable of predicting the consequences of actions, thus, is better at planning sequences of actions to solve tasks under different circumstances.
DOI
https://doi.org/10.7275/12657464
Recommended Citation
Ku, Li Yang, "Integration of Robotic Perception, Action, and Memory" (2018). Doctoral Dissertations. 1364.
https://doi.org/10.7275/12657464
https://scholarworks.umass.edu/dissertations_2/1364
Included in
Artificial Intelligence and Robotics Commons, Cognitive Neuroscience Commons, Robotics Commons