Robot Environment Mapping for User-Directed Object Handling
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Solution Overview
Problem
Current robot navigation systems, such as random bounce methods and rudimentary navigation systems, are inefficient and often miss cleaning large areas, and require human intervention for unknown objects or obstacles, which is inconvenient.
Innovation Solution
A method and apparatus that allow users to control robots through an electronic device, receiving environmental data, displaying a graphical representation, and transmitting control data to move objects or perform actions, enabling users to direct robots to desired locations or perform tasks like cleaning without requiring pre-existing knowledge of the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If random bounce navigation method is used, then the robot can navigate without pre-existing knowledge of the environment, but large areas of the floor are completely missed and cleaning efficiency is poor
Solution Approach 1:
The system performs preliminary mapping and object detection before cleaning tasks. The robot first navigates to detect and map the environment, identify objects and their locations, then uses this pre-acquired information to plan efficient cleaning paths that systematically cover all areas rather than using random bounce methods
Solution Approach 2:
The system continuously receives feedback from sensors about the robot's location, detected objects, and cleaning progress. This feedback is used to dynamically adjust the navigation path and cleaning strategy in real-time, ensuring complete coverage while maintaining high efficiency throughout the cleaning process
2Productivity
If SLAM techniques are used, then the robot can achieve more systematic navigation patterns and efficiently clean the required area, but the system complexity increases
Solution Approach 1:
The navigation system is segmented into distinct functional modules: SLAM-based mapping module, object detection module, path planning module, and control module. Each module performs a specific function and can be independently optimized or replaced, reducing overall system complexity while maintaining high cleaning efficiency
Solution Approach 2:
The system uses a unified SLAM framework that simultaneously performs navigation, mapping, and object location detection. This multi-functional approach eliminates the need for separate systems for each task, reducing overall complexity while achieving systematic navigation and efficient cleaning
3Extent of automation
If the robot autonomously encounters unknown objects, then the robot can operate without human assistance, but it cannot know how to process such objects and requires human intervention
Solution Approach 1:
The robot autonomously detects, identifies, and processes unknown objects using integrated sensors and object recognition algorithms. When an unknown object is detected, the system automatically determines its category, selects appropriate processing actions (move, clean around, avoid), and executes them without requiring human intervention, thereby maintaining both high automation and user convenience
Solution Approach 2:
The system continuously monitors the environment for unknown objects and provides real-time feedback about detected objects to the control system. This feedback loop enables the robot to autonomously adapt its behavior when encountering new objects, maintaining autonomous operation while handling diverse situations
4Reliability
If human intervention is required for object identification and movement decisions, then the robot can handle unknown objects appropriately, but the user experience becomes burdensome
Solution Approach 1:
The robot autonomously performs object identification, classification, and decision-making for object handling. The system uses sensors and algorithms to automatically determine what actions to take with detected objects, eliminating the need for continuous human intervention while maintaining reliable and accurate object handling
Solution Approach 2:
The system performs preliminary object detection, identification, and path planning before executing cleaning or object manipulation tasks. By pre-processing and pre-planning actions, the robot ensures reliable object handling while operating autonomously without requiring user input during task execution
Data Source
AI summary
Measures for use in controlling a robot. At an electronic user device, data representative of an environment of the robot is received from the robot. The received data indicates a location of at least one moveable object in the environment. In response to receipt of the representative data, a representation of the environment of the robot is displayed on a graphical display of the electronic user device. Input is received from a user of the electronic user device indicating a desired location for the at least one moveable object in the environment of the robot. In response to receipt of the user input, control data is transmitted to the robot. The control data is operable to cause the robot to move the at least one object to the desired location in the environment of the robot.