Dynamic Robot Navigation With Rangefinder-Only Object Tracking
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Solution Overview
Problem
Autonomous mobile robots face challenges in navigating dynamic environments with minimal sensors while ensuring user privacy, as they often rely on multiple sensors for accurate navigation and object tracking, which raises concerns about data privacy and security.
Innovation Solution
An intelligent remote sensing system utilizing a rangefinder sensor as a perception sensor and an inertial measurement unit as an orientation sensor, employing Simultaneous Localization and Mapping (SLAM), Recurrent Neural Networks (RNN) for object detection, and Kalman filters for trajectory prediction, allowing autonomous navigation with minimal sensor usage and maintaining user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are used for accurate navigation and object tracking, then navigation accuracy and object detection reliability are improved, but device complexity and user privacy concerns increase
Solution Approach 1:
The patent extracts and removes the camera sensor from the sensor suite, retaining only the rangefinder and IMU. This extraction principle reduces device complexity and privacy concerns while maintaining navigation accuracy through alternative means (SLAM algorithms and inertial navigation) and object tracking through radar-like rangefinder capabilities.
Solution Approach 2:
The rangefinder sensor is made multi-functional by using it for both navigation (via SLAM) and object detection/tracking. This universal usage reduces the need for separate specialized sensors, thereby reducing overall device complexity while maintaining reliability in both navigation and object tracking functions.
2Difficulty of detecting and measuring
If multiple sensors including camera are used, then object detection capability is improved, but user privacy protection deteriorates
Solution Approach 1:
The camera sensor, which poses privacy risks, is extracted and removed from the system. Object detection capability is maintained through the rangefinder sensor combined with SLAM and tracking algorithms that can detect and track objects without capturing visual images, thus eliminating privacy concerns.
Solution Approach 2:
The optical detection system (camera) is replaced with a radar-like electromagnetic detection system (rangefinder). This substitution maintains object detection capability through electromagnetic wave reflection and time-of-flight measurement while avoiding the privacy issues associated with visual image capture.
3Device complexity
If minimal sensors are used, then device complexity is reduced, but navigation reliability in dynamic environments deteriorates
Solution Approach 1:
The patent changes the processing parameters and algorithms rather than adding sensors. Advanced SLAM algorithms, Kalman filters for state estimation, and momentum-based prediction methods are employed to extract maximum navigation reliability from the minimal sensor set of rangefinder and IMU.
Solution Approach 2:
Algorithmic intermediaries (SLAM, Kalman filters, prediction algorithms) are introduced to bridge the gap between minimal sensor inputs and reliable navigation outputs. These software intermediaries process and fuse sensor data to achieve navigation reliability comparable to systems with more sensors.
Data Source
AI summary
An operating method for navigating a device in a dynamic environment is provided. The method includes building a map based on sensor data, localizing a position of the device on the map based on the sensor data, determining a first position of a moving object on the map based on the sensor data, determining a momentum of the moving object, determining a second position of the moving object on the map based on the determined momentum, and changing the position of the device based on the determined second position of the moving object and a position of at least one obstacle.