Companion Robot Outdoor Navigation via Modular Sensing
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Solution Overview
Problem
Current companion robots are primarily designed for indoor use and lack widespread adoption for outdoor applications, failing to provide effective navigation and assistance in outdoor environments.
Innovation Solution
A companion robot system equipped with a sensing unit, positioning unit, scanning unit, network unit, input unit, and processor, which includes modules for controlling movement, recognizing user input, and generating safe walking paths, enabling the robot to navigate outdoors and adapt to user preferences and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If companion robots are designed for indoor use only, then they can maintain simpler navigation systems, but they cannot provide outdoor navigation and assistance
Solution Approach 1:
The navigation system is divided into multiple independent modules: a sensing unit for obstacle detection, a positioning unit for location tracking, and a scanning unit for environmental mapping. Each module operates independently but contributes to the overall navigation function, allowing the robot to handle complex outdoor environments through coordinated modular components.
Solution Approach 2:
The navigation system is designed to perform multiple functions simultaneously: obstacle avoidance, path planning, location tracking, and environmental adaptation. This multi-functional approach allows a single integrated system to replace what would otherwise require separate specialized systems, resolving the contradiction between versatility and complexity.
2Measurement precision
If the robot incorporates multiple sensing and positioning units for outdoor navigation, then navigation accuracy improves, but device complexity increases
Solution Approach 1:
Multiple sensing units (obstacle sensors, positioning sensors, scanning devices) are merged into a single integrated navigation system controlled by one processor. This consolidation allows the robot to achieve high navigation accuracy through coordinated data from multiple sources while managing system complexity through unified control architecture.
Solution Approach 2:
The processor acts as an intermediary that receives and integrates data from multiple sensing units, positioning units, and scanning units. It processes this information centrally to generate navigation decisions, allowing individual sensors to remain relatively simple while achieving complex navigation functionality through intelligent data integration.
3Reliability
If the robot adjusts speed and generates safe walking paths in real-time, then user safety improves, but processing requirements and energy consumption increase
Solution Approach 1:
The scanning unit performs preliminary environmental scanning and path planning before the robot begins movement. By pre-processing the environment data and identifying safe paths in advance, the system reduces the real-time processing burden during actual navigation, thereby lowering energy consumption while maintaining safety.
Solution Approach 2:
The robot performs obstacle detection and path verification at periodic intervals rather than continuously. This periodic scanning approach, combined with predictive path planning, ensures user safety through regular monitoring while significantly reducing energy consumption compared to continuous real-time processing.
Data Source
AI summary
A companion robot includes a body, a sensing unit, a positioning unit, a network unit, an input unit, a storage device, and at least one processor. The processor controls the companion robot to receive a destination, generate a walking path of the companion robot according to the destination and a current location of the companion robot, obtain a walking direction and a walking speed of a user, and control the companion robot to walk along the walking path according to the walking direction and the walking speed.