Robot Object Interaction Mapping for Low-Code Navigation Setup
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current robot navigation systems require significant operator input for configuring interactions with environmental objects, making the setup process laborious and limiting the robot's usability due to the need for coding expertise, which delays deployment and affects user-friendliness.
Innovation Solution
A computer-implemented method and robot system that uses sensor data to detect objects, author interaction behaviors, and generate a localization map, allowing operators to select and execute preconfigured behaviors through a graphical interface, reducing the need for complex coding and enhancing intuitive operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If robot navigation systems use traditional configuration methods requiring operator input for configuring interactions with environmental objects, then the robot can perform precise interactions, but the setup process becomes laborious and requires coding expertise
Solution Approach 1:
The robot autonomously detects objects in the environment using sensor data and automatically generates interaction behaviors without requiring operator configuration. The system self-configures by matching detected objects with pre-defined behavior templates, eliminating the need for operators to write code or manually configure interaction parameters.
Solution Approach 2:
The system pre-configures multiple interaction behavior templates for common object types before deployment. When an object is detected, the robot selects and applies the appropriate pre-configured template, avoiding the need for real-time coding or complex configuration during operation.
2Productivity
If robot navigation systems require significant operator input for configuring interactions, then precise control is achieved, but deployment time increases and user-friendliness decreases
Solution Approach 1:
The robot autonomously detects objects in the environment using sensor data and automatically generates interaction behaviors without requiring operator configuration. The system self-configures by matching detected objects with pre-defined behavior templates, eliminating the need for operators to write code or manually configure interaction parameters.
Solution Approach 2:
The system pre-configures multiple interaction behavior templates for common object types before deployment. When an object is detected, the robot selects and applies the appropriate pre-configured template, avoiding the need for real-time coding or complex configuration during operation.
3Adaptability or versatility
If the robot system automatically detects objects and generates interaction behaviors, then ease of operation improves, but the system must process and interpret sensor data autonomously
Solution Approach 1:
The robot autonomously detects objects in the environment using sensor data and automatically generates interaction behaviors without requiring operator configuration. The system self-configures by matching detected objects with pre-defined behavior templates, eliminating the need for operators to write code or manually configure interaction parameters.
Solution Approach 2:
The system pre-configures multiple interaction behavior templates for common object types before deployment. When an object is detected, the robot selects and applies the appropriate pre-configured template, avoiding the need for real-time coding or complex configuration during operation.
Data Source
AI summary
A method includes receiving sensor data for an environment about the robot. The sensor data is captured by one or more sensors of the robot. The method includes detecting one or more objects in the environment using the received sensor data. For each detected object, the method includes authoring an interaction behavior indicating a behavior that the robot is capable of performing with respect to the corresponding detected object. The method also includes augmenting a localization map of the environment to reflect the respective interaction behavior of each detected object.