Autonomous Motion Planning With Hierarchical Logical Expressions
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Solution Overview
Problem
Existing technologies for autonomous motion planning lack efficient methods to translate basic principles into logical expressions that can guide motion actions, leading to suboptimal decision-making and potential deviations from intended actions.
Innovation Solution
The method involves analyzing data associated with basic principles to generate logical expressions, which are then organized into priority groups and hierarchies to plan motion actions for machines with autonomous capabilities. This includes parsing texts, inferring conditions and actions, tracking objects, and statistically evaluating occurrences to adjust logical expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If basic principles are directly applied to motion planning, then the system maintains simplicity in decision-making, but the system lacks precision in translating principles into actionable logical expressions
Solution Approach 1:
The patent segments the motion planning process into distinct modules: a principle analyzer that parses basic principles into logical expressions, a hierarchy organizer that structures expressions by priority, and a motion planner that executes actions. This segmentation transforms the vague process of applying principles into precise, actionable steps while maintaining overall system clarity.
Solution Approach 2:
The patent introduces logical expressions as intermediary elements between basic principles and motion actions. These expressions serve as a formal bridge that translates natural language principles into structured, computable conditions and actions, enhancing precision without requiring the entire system to become overly complex.
2Manufacturing precision
If the system uses detailed logical expressions with multiple priority groups and hierarchies, then motion planning precision improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-organizing logical expressions into hierarchical priority groups before motion planning execution. This pre-structuring allows the system to quickly access and evaluate expressions in order of importance during real-time operation, reducing computational overhead while maintaining high precision in motion decisions.
Solution Approach 2:
The patent implements dynamics by allowing the hierarchy of logical expressions to be adaptively adjusted based on operating conditions. The system can dynamically reprioritize expressions or modify their applicability based on sensor data and context, enabling precise motion planning that responds efficiently to changing environments without rigid computational overhead.
3Reliability
If the system comprehensively analyzes all basic principles and organizes them into complete hierarchies, then decision-making accuracy improves, but the system becomes less adaptable to new or unexpected situations
Solution Approach 1:
The patent applies dynamics by designing a flexible hierarchy structure where logical expressions can be dynamically added, removed, or reprioritized based on new information. The system maintains reliable decision-making through established hierarchies while adapting to new situations by incorporating new principles into the existing framework without requiring complete restructuring.
Solution Approach 2:
The patent implements universality by creating a general-purpose logical expression framework that can accommodate various types of basic principles (ethical, legal, operational, environmental). This universal structure allows the system to reliably handle diverse situations by mapping new principles into the existing hierarchical framework, enhancing both reliability and adaptability.
4Reliability
If the system evaluates deviation metrics for each motion action, then compliance with proper actions is ensured, but the computational load and energy consumption increase
Solution Approach 1:
The patent applies partial action by evaluating deviation metrics selectively rather than for every possible motion parameter. The system focuses computational resources on evaluating only the most critical deviations from proper actions based on the hierarchical priority structure, ensuring compliance with essential requirements while reducing overall computational load and energy consumption.
Solution Approach 2:
The patent implements feedback by using deviation metric evaluations to continuously refine motion planning decisions. The system evaluates compliance, feeds this information back into the decision-making process, and adjusts subsequent actions accordingly. This targeted feedback mechanism ensures reliable compliance while minimizing energy expenditure by focusing evaluations on critical deviations rather than all parameters.
Data Source
AI summary
Among other things, planning a motion of a machine having moving capabilities is based on strategic guidelines derived from various basic principles, such as laws, ethics, preferences, driving experiences, and road environments.