Robot SLAM Navigation Using Multi-Sensor Obstacle Mapping
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Solution Overview
Problem
Existing autonomous robots face challenges in efficiently navigating and mapping environments, particularly in avoiding obstacles and creating accurate maps in real-time.
Innovation Solution
The implementation of a Light Weight Real Time SLAM Navigational Stack that enables robots to detect obstacles, adjust their path, and generate a planar representation of their workspace using data from multiple sensors, allowing for real-time navigation and mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional SLAM algorithms are used for real-time navigation and mapping, then accurate environment maps can be generated, but computational burden increases and processing speed decreases
Solution Approach 1:
The patent segments the SLAM problem into distinct functional modules: sensor data acquisition, feature point detection, coordinate transformation, and map generation. By dividing the computational task into separate processing stages, each handling specific aspects of the navigation problem, the system reduces overall computational complexity while maintaining mapping accuracy.
Solution Approach 2:
The patent extracts and processes only the most critical features from sensor data - specifically identifying and tracking key feature points rather than processing all raw sensor information. This selective extraction of essential information reduces computational burden while preserving the accuracy needed for effective navigation and mapping.
2Reliability
If multiple sensors are used for obstacle detection and path planning, then navigation reliability improves, but device complexity and processing requirements increase
Solution Approach 1:
The patent merges data from multiple sensor types (cameras, LIDAR, depth sensors) into a unified processing framework. By integrating sensor inputs and processing them through common algorithms for obstacle detection and path planning, the system achieves reliable navigation while avoiding the complexity of completely separate processing chains for each sensor type.
Solution Approach 2:
The patent implements universal processing algorithms that can handle data from different sensor types through a common interface. The same feature detection, coordinate transformation, and path planning algorithms work with inputs from various sensors, reducing system complexity while maintaining the reliability benefits of multi-sensor integration.
Data Source
AI summary
A memory storing program code that when executed by a processor of a robot effectuates operations, including: detecting, with a sensor of a plurality of sensors disposed on the robot, an object in a line of sight of the sensor; adjusting, with the processor of the robot, a current path of the robot to detour around or avoid the object; generating, with the processor of the robot, a planar representation of a workspace of the robot based on data collected by at least some sensors of the plurality of sensors; and wherein an application of a communication device paired with the robot is configured to display the planar representation.