Sensor Fusion Localization for Adaptive Robot Coverage Paths

The patent implements dynamic path adjustment by continuously modifying the mowing path based on real-time sensor data. The controller receives localization data from multiple sensors and dynamically adjusts the coverage path to account for actual position deviations and dynamic obstacles, transforming a static path plan into an adaptive, living trajectory that ensures complete coverage despite initial planning simplifications.

The system employs feedback loops where localization data from UWB, GPS, and IMU sensors continuously monitors the robot's actual position and feeds this information back to the path planning module. This feedback mechanism enables the system to detect deviations from the planned path and generate corrective adjustments, ensuring that incomplete coverage areas are identified and re-mowed.

The patent combines multiple localization sensors (UWB, GPS, IMU) into a unified sensor fusion system. By merging the data from these different sensor types, the system achieves superior localization accuracy that exceeds what any single sensor could provide alone. The controller integrates measurements from all sensors to compute the robot's position, effectively combining their strengths while managing their combined energy footprint.

The localization system serves multiple functions simultaneously: it provides position estimation for path following, detects dynamic obstacles, enables coverage monitoring, and supports navigation. This multi-functionality justifies the energy investment in multiple sensors, as they are not merely adding capability but rather enabling a suite of critical functions that collectively improve overall system efficiency and effectiveness.

The system applies partial re-mowing rather than complete area re-coversion. By using localization accuracy data to identify specific regions that are likely uncovered or partially covered, the robot performs targeted re-mowing only in those problematic areas. This partial action approach ensures coverage completeness without the excessive time penalty of re-mowing entire lawns, balancing thoroughness with operational efficiency.

The system performs preliminary localization and coverage assessment before executing re-mowing operations. By using sensor fusion to predict which areas are likely uncovered based on localization errors and path deviations, the system proactively identifies re-mowing candidates in advance. This preliminary identification allows for optimized re-mowing routes that minimize travel time and battery consumption while ensuring all necessary areas are covered.