Syntactic Inferential Motion Planning for Robots
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Solution Overview
Problem
Current robotic planning systems are inflexible, computationally intensive, and require complex geometric modeling, making them difficult to adapt to changing environments and implement efficiently, while also failing to effectively avoid collisions and singularities during robot motion.
Innovation Solution
A Syntactic Inferential Motion Planning (SIMPL) methodology that uses a set of syntactic rules to plan robot motion between programmed points, optimizing routes based on predetermined criteria and incorporating an error recovery algorithm to handle unexpected conditions, without the need for hand-coded scripts or complete geometric modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex geometric modeling is used to plan robot motion, then motion accuracy and safety are improved, but computational complexity and processing requirements increase enormously
Solution Approach 1:
The workspace is segmented into discrete grid cells rather than using continuous geometric modeling. This discretization divides the complex continuous space into manageable discrete units, reducing computational complexity while maintaining sufficient accuracy for collision detection and path planning.
Solution Approach 2:
The patent uses simplified grid-based representations instead of detailed geometric models. These simplified models require minimal computational resources and can be quickly processed, sacrificing some geometric precision for significant gains in computational efficiency and real-time performance.
2Ease of manufacture
If hand-coded scripts are used to control robot motion, then implementation simplicity is improved, but adaptability to environmental changes deteriorates
Solution Approach 1:
The robot system performs self-planning by automatically generating motion paths based on grid-based environmental representation and syntactic rules. Instead of relying on pre-programmed scripts, the system autonomously determines valid motion sequences, enabling adaptability to changing environments while maintaining implementation simplicity through rule-based automation.
Solution Approach 2:
The motion planning system is dynamic and adaptive, allowing the robot to recalculate paths in response to environmental changes. The grid-based representation and syntactic rule system enable real-time replanning, making the system flexible and adaptable rather than static and rigid.
3Reliability
If formal motion patterns are enforced to ensure safety, then collision avoidance is improved, but ability to exploit fortuitous geometry deteriorates
Solution Approach 1:
The patent changes the representation parameters from continuous geometric coordinates to discrete grid cells. This parameter transformation allows the system to maintain safety through systematic grid-based collision checking while enabling more efficient and direct motion paths that can exploit favorable geometric configurations without being constrained by formal rigid patterns.
Data Source
AI summary
A method and system for planning and optimizing the movement of a robotic device comprises establishing a plurality of spatial locations where the device can possibly be positioned and establishing rule sets for constraining movement of the robotic device between the locations. Once a start and end point have been determined, the method of the invention calculates all possible routes for the device to move, via the established locations and following the constraints of the rule sets. The calculated routes are then compared to a criteria, such as minimizing time, and an optimum route, meeting the desired criteria is determined. The calculated routes may also be cached for future access. The invention also provides for an error recovery method for allowing a robotic device to recover should it encounter an error.