Mobile Robot Sensor Adaptation for Dynamic Navigation
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Solution Overview
Problem
Existing mobile robot navigation and safety systems are limited by simple kinematic and dynamic models, leading to conservative operation and inflexible safety controls that do not account for payloads, resulting in inefficient navigation and increased costs due to manual configuration requirements.
Innovation Solution
The system adapts sensor operation to prioritize data capture in critical sensor regions defined by angular and linear velocities, payload, and environmental conditions, allowing for more flexible and efficient navigation by adjusting sensor ranges and trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple kinematic and dynamic models are used for navigation, then system complexity is reduced, but navigation efficiency and performance deteriorate due to conservative constraints
Solution Approach 1:
The patent implements dynamic sensor operation where detection regions and sampling rates are continuously adjusted based on real-time robot velocity (angular and linear). This dynamic adaptation allows the system to operate closer to physical limits while maintaining safety, resolving the contradiction between system complexity and navigation efficiency by making the system adaptive rather than statically complex
Solution Approach 2:
The system changes operational parameters (sensor detection region size, sensor sampling rate) based on robot velocity states. At higher velocities, the system expands detection regions and increases sampling rates, while at lower velocities it reduces them. This parameter adaptation enables efficient navigation without requiring permanently complex system architecture
2Device complexity
If highly discretized states are used in safety systems, then system simplicity is maintained, but performance and flexibility deteriorate
Solution Approach 1:
The safety system dynamically adjusts sensor operation based on continuous velocity measurements rather than discrete states. The detection region and sampling rate continuously adapt to the robot's current velocity, providing flexible and precise safety control without relying on highly discretized states, thus maintaining both simplicity and flexibility
3Adaptability or versatility
If manual configuration is required for safety systems, then system adaptability is reduced, but configuration precision can be controlled, however operational costs increase
Solution Approach 1:
The system performs self-configuration by automatically determining appropriate sensor detection regions and sampling rates based on real-time velocity measurements. This self-service capability eliminates the need for manual configuration while adapting to different operating conditions, reducing operational costs and increasing adaptability simultaneously
4Reliability
If sensor detection regions are expanded to cover all potential collision zones, then safety is improved, but energy consumption and data processing load increase
Solution Approach 1:
The system applies local quality by concentrating sensor detection resources in critical regions determined by current velocity. Instead of uniformly expanding detection regions everywhere, the system selectively focuses sensing capacity on directions and distances most relevant to current motion, improving safety where needed while reducing energy consumption in less critical areas
Solution Approach 2:
The system applies partial action by activating enhanced detection only when and where necessary based on velocity thresholds. At low velocities, reduced detection regions suffice, while at high velocities, expanded detection is applied selectively. This avoids the excessive energy consumption of maintaining full detection coverage at all times
Data Source
AI summary
Systems and methods for operating a mobile robot is disclosed. The system can include a processor and a plurality of sensors mounted on the mobile robot. The method includes operating the mobile robot to autonomously navigate along a trajectory. While the mobile robot autonomously navigates along the trajectory, the method involves operating the processor to: monitor an angular velocity and a linear velocity of the mobile robot; determine one or more critical sensor regions defined with reference to the mobile robot based at least on the angular velocity and the linear velocity of the mobile robot; and adapt the operation of the plurality of sensors to prioritize capture of sensor data within the one or more critical sensor regions. Each sensor can be operable to capture the sensor data for an adjustable detection region defined with respect to the sensor and the mobile robot.