Tele-Operated Robot Path Planning with UAV Obstacle Mapping
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Solution Overview
Problem
Existing tele-operated robots lack efficient methods for outdoor property maintenance, such as lawn care and landscaping, due to limitations in navigation and obstacle avoidance in complex outdoor environments.
Innovation Solution
A method involving the use of an unmanned aerial vehicle (UAV) to obtain aerial images of the property, which are then analyzed at a control center to determine autonomously navigable areas and schedule the operation of a tele-operated robot for maintenance tasks, while also enabling obstacle avoidance through sensor data and UAV-assisted imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tele-operated robots are used for outdoor property maintenance, then labor hours and total time spent can be minimized, but navigation and obstacle avoidance in complex outdoor environments remain problematic
Solution Approach 1:
The patent introduces an intermediary system consisting of UAVs, sensors, and a control center that mediates between the tele-operated robot and the complex outdoor environment. The UAV captures aerial images and the control center processes this data to generate navigation paths and obstacle avoidance instructions, enabling the robot to operate reliably in environments that would otherwise be too complex for direct tele-operation or full autonomy
Solution Approach 2:
The system performs preliminary actions by capturing aerial images of the property beforehand and processing this data at the control center to identify navigable areas and obstacles before the robot begins its maintenance task. This advance preparation enables the robot to follow pre-planned paths and avoid obstacles without requiring real-time complex decision-making
2Productivity
If aerial images are obtained and analyzed at a control center to determine autonomously navigable areas, then the schedule of operation can be optimized, but device complexity increases
Solution Approach 1:
The system segments the property maintenance task into distinct phases: aerial image capture by UAV, image processing and analysis at the control center, path planning, and execution by the robot. This segmentation allows each component to specialize in its function, with the control center handling complex processing while the robot focuses on execution, thereby optimizing productivity without overwhelming any single device
Solution Approach 2:
The control center automatically processes aerial images to identify navigable areas and generate operation schedules without requiring manual intervention. The system serves itself by autonomously converting raw image data into actionable navigation paths and maintenance schedules, reducing the need for human operators while improving scheduling efficiency
Data Source
AI summary
A robot includes an optical marker disposed to be visible in a top-view image of the robot, a receiver configured to receive a top-down image of an area of interest surrounding the robot within a property, and a processor configured to distinguish the robot from structural features on the property based on an image of the optical marker. A position and an orientation of the robot and the structural features relative to the property is determined based on the top-down image. Among the structural features, a subset of features classified as obstacles inhibiting an operation of the robot as the robot moves within the area of interest is determined. An operating path for the robot within the area of interest so as to avoid the obstacles is then determined.