Visual programming for mobile robot navigation using high-level landmarks

We propose a visual programming system that allows users to specify navigation tasks for mobile robots using high-level landmarks in a virtual reality (VR) environment constructed from the output of visual simultaneous localization and mapping (vSLAM). The VR environment provides a Google Street View-like interface for users to familiarize themselves with the robot's working environment, specify high-level landmarks, and determine task-level motion commands related to each landmark. Our system builds a roadmap by using the pose graph from the vSLAM outputs. Based on the roadmap, the high-level landmarks, and task-level motion commands, our system generates an output path for the robot to accomplish the navigation task. We present data structures, architecture, interface, and algorithms for our system and show that, given n s search-type motion commands, our system generates a path in O(n s (n r logn r +m r )) time, where n r and m r are the number of roadmap nodes and edges, respectively. We have implemented our system and tested it on real world data.

Authors

• Joseph Lee
• Yan Lu
• Yiliang Xu
• Dezhen Song

Keywords

• Mobile robots
• Navigation
• Cameras
• Visualization
• Robot vision systems
• Sequential analysis
• Mobile Robot
• Robot Navigation
• Visual Programming
• Real-world Data
• Navigation Task
• Simultaneous Localization And Mapping
• Robotic Tasks
• Image Regions
• Undirected
• Shortest Path
• Graphical User Interface
• Bounding Box
• Path Planning
• Depth Camera
• Robot Motion
• Vision Sensors
• Camera Pose
• Supervisory Control
• Transition Conditions
• View Of The Scene
• Motion Sequences
• Robot Programming
• Priority Map
• Panoramic Images
• Path Generation
• Automatic Program
• Virtual Tourism
• Intersection Point