Improving Autonomous Robotic Navigation Using Imitation Learning
dc.contributor.author | Cèsar-Tondreau, Brian | en |
dc.contributor.author | Warnell, Garrett | en |
dc.contributor.author | Stump, Ethan | en |
dc.contributor.author | Kochersberger, Kevin B. | en |
dc.contributor.author | Waytowich, Nicholas R. | en |
dc.date.accessioned | 2021-09-02T17:44:47Z | en |
dc.date.available | 2021-09-02T17:44:47Z | en |
dc.date.issued | 2021-06-01 | en |
dc.description.abstract | Autonomous navigation to a specified waypoint is traditionally accomplished with a layered stack of global path planning and local motion planning modules that generate feasible and obstacle-free trajectories. While these modules can be modified to meet task-specific constraints and user preferences, current modification procedures require substantial effort on the part of an expert roboticist with a great deal of technical training. In this paper, we simplify this process by inserting a Machine Learning module between the global path planning and local motion planning modules of an off-the shelf navigation stack. This model can be trained with human demonstrations of the preferred navigation behavior, using a training procedure based on Behavioral Cloning, allowing for an intuitive modification of the navigation policy by non-technical users to suit task-specific constraints. We find that our approach can successfully adapt a robot’s navigation behavior to become more like that of a demonstrator. Moreover, for a fixed amount of demonstration data, we find that the proposed technique compares favorably to recent baselines with respect to both navigation success rate and trajectory similarity to the demonstrator. | en |
dc.description.version | Published version | en |
dc.format.extent | 10 pages | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Cèsar-Tondreau B, Warnell G, Stump E, Kochersberger K and Waytowich NR (2021) Improving Autonomous Robotic Navigation Using Imitation Learning. Front. Robot. AI 8:627730. doi: 10.3389/frobt.2021.627730 | en |
dc.identifier.doi | https://doi.org/10.3389/frobt.2021.627730 | en |
dc.identifier.uri | http://hdl.handle.net/10919/104917 | en |
dc.identifier.volume | 8 | en |
dc.language.iso | en | en |
dc.publisher | Frontiers Media | en |
dc.rights | Creative Commons Attribution 4.0 International | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en |
dc.subject | autonomous navigation | en |
dc.subject | learning from demonstration | en |
dc.subject | imitation learning | en |
dc.subject | human in the loop | en |
dc.subject | robot learning and behavior adaptation | en |
dc.title | Improving Autonomous Robotic Navigation Using Imitation Learning | en |
dc.title.serial | Frontiers in Robotics and AI | en |
dc.type | Article - Refereed | en |
dc.type.dcmitype | Text | en |
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