IARN

Indoor Autonomous Robot Navigation

Hospitals and Hospice Care

Parameters

  • 6 Months
  • Starts in August 2020
  • ~15 collaborators

“Learning Navigation Behaviors End-to-End with AutoRL,” “PRM-RL: Long-Range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning”, and “Long-Range Indoor Navigation with PRM-RL”

Primary Functions

  • Point-to-Point Long-range Navigation
  • Path Following / Guided Navigation
  • Collision avoidance

Technologies

ROS

  • Framework for simulating complex robot behavior
  • Pose Estimation, Localization, and Navigation
  • Transfer learned parameters to real world

SLAM

  • Simultaneous localization and mapping
  • Creating a map of environment and tracking robot position 
  • ROS includes tools for SLAM - gmapping

 

SLAM

Robot Platform

TurtleBot 3 Burger

LiDAR Camera

Reinforcement Learning

Reinforcement Learning

  • State : noisy LiDAR observations
  • Action : Differential Drive Wheel Speeds
  • Reward : Reach goal while avoiding obstacles

Secondary Tasks

Monitoring and Debugging

  • Monitor and Log state-action information
  • Real-time visualization of trajectories

Web/Mobile Interface

  • Track the status of the robot
  • Sensors, Battery, etc,
  • Control 

On-board UI

  • Secure Access
  • Control
  • Networking
  • Intervention/Reset

IARN

By Suriyadeepan R

IARN

  • 290
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