Robot Landing Zone Evaluation Using Feasible Cell Clusters
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Solution Overview
Problem
Existing autonomy systems for robots are limited in extensibility and adaptability, as they are typically designed to address only one aspect of robot operation, such as automatic control or route planning, and are not well-equipped for rapid adaptation to new platforms or the addition of new modules.
Innovation Solution
A computer-implemented method that tessellates a ground region into cells classified as feasible or infeasible for landing, searches for clusters of adjoining feasible cells, ranks sub-regions based on a cost metric, and selects a sub-region for robotic landing, using terrain data to evaluate feasibility and output geographic positions for guidance, navigation, or control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If existing autonomy systems are designed to address only one aspect of robot operation, then the system design can be focused and simplified, but the extensibility and adaptability of the system are limited
Solution Approach 1:
The patent applies universality by creating an autonomy system architecture that can perform multiple functions: automatic control, route planning, and landing zone selection. The system is designed with modular components that can be configured for different robot platforms and mission types, allowing a single system to address multiple aspects of robot operation rather than being limited to one function.
Solution Approach 2:
The patent applies segmentation by dividing the autonomy system into separate functional modules (automatic control module, route planning module, landing zone selection module). This modular architecture allows each module to be independently developed, tested, and adapted, improving extensibility while maintaining manageable complexity through clear module interfaces.
2Manufacturing precision
If existing autonomy systems are designed to address only one aspect of robot operation, then the underlying algorithms and software architecture can be optimized for that specific task, but the system is not well-equipped to support the addition of new modules
Solution Approach 1:
The patent applies dynamics by creating a flexible software architecture where modules can be dynamically added, removed, or reconfigured based on mission requirements. The system supports runtime module registration and configuration, allowing new modules to be integrated without requiring complete system redesign, thus maintaining algorithm optimization while enabling modular extensibility.
3Reliability
If existing autonomy systems are not structured for rapid adaptation to new platforms, then the system can be optimized for a specific platform, but the system cannot quickly adapt to new robotic platforms through parameterization
Solution Approach 1:
The patent applies parameter changes by implementing a parameterized platform interface that allows the same autonomy system to adapt to different robotic platforms through configuration parameters rather than code changes. The system accepts platform-specific parameters (dimensions, capabilities, constraints) and automatically adjusts its behavior, enabling rapid adaptation while maintaining reliability through proven algorithms.
Data Source
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AI summary
A method of supporting robot(s) landing within a ground region is provided. The method includes accessing a map in which the ground region is tessellated into cells covering respective areas of the ground region. Each cell is classified as feasible to indicate a respective area is feasible for landing, or infeasible to indicate the respective area is infeasible for landing. The map is searched for clusters of adjoining cells that are classified as feasible, covering clusters of adjoining areas that define sub-regions within the ground region that are feasible for landing. The sub-regions are ranked according to a cost metric, and one of the sub-regions is selected according to the ranking. A geographic position of the selected sub-region is then output for use in at least one of guidance, navigation or control of the robot(s) to land at the selected sub-region within the ground region.