Discrete State Transition Mapping for Multi-Agent Robotic Systems
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Solution Overview
Problem
Existing robotic systems with continuous motion paths have an infinite number of states, making it difficult to determine all possible error cases and transitions, especially in systems with multiple agents, leading to potential interruptions and inefficiencies.
Innovation Solution
A method to determine possible direct transitions between discrete system states by defining rules, nodes, and edges, allowing for offline evaluation and optimization of transitions, which are then collected into a look-up table for fast runtime decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If continuous motion paths are used in robotic systems, then the system can perform smooth and flexible movements, but the number of states becomes infinite making it difficult to determine all possible error cases and transitions
Solution Approach 1:
The continuous motion path is segmented into discrete states by defining a state space where each state represents a specific configuration of the robotic system. This segmentation transforms the infinite continuous states into a manageable finite set of discrete states, enabling systematic analysis of all possible error cases and transitions.
Solution Approach 2:
The patent performs preliminary analysis by defining all possible states and transitions before the robotic system operates. By pre-determining the state space and possible transitions offline, the system prepares a comprehensive map of error cases and valid transitions, eliminating the need for complex real-time analysis during operation.
2Reliability
If discrete states are defined for robotic agents, then all possible error cases can be determined, but the programming process becomes iterative and time-consuming
Solution Approach 1:
The system automatically generates the state transition model by evaluating the defined states and transitions without requiring manual programming of each error case. The automated evaluation process systematically determines all possible transitions and error cases, reducing programming time while maintaining comprehensive error coverage.
Solution Approach 2:
By performing the state transition analysis offline before deployment, the system prepares a complete error handling framework in advance. This preliminary action eliminates the need for iterative debugging and testing during operation, significantly reducing the overall programming and commissioning time.
3Speed
If all states and transitions are determined offline, then fast runtime decisions are enabled, but the initial setup and evaluation process becomes complex
Solution Approach 1:
The offline evaluation process is segmented into manageable steps: defining states, defining transitions, and evaluating connectivity. This structured approach breaks down the complex evaluation into systematic tasks that can be automated and executed efficiently, reducing the perceived complexity while enabling fast runtime performance.
4Adaptability or versatility
If multiple agents are used in the robotic system, then task capability is enhanced, but the number of possible states and error cases increases dramatically
Solution Approach 1:
The system segments the multi-agent state space by defining discrete states for each agent independently, then combining them systematically. This segmentation approach allows the complex multi-agent state space to be broken down into manageable components that can be evaluated methodically, preventing exponential complexity from overwhelming the analysis process.
Data Source
AI summary
A method for determining possible transitions of system states in an industrial system with a plurality of agents with discrete agent states. The method comprises the steps of defining a plurality of rules, each rule comprising a pre-condition of at least one agent state that is to be changed, a post-condition of the at least one agent state, and an action or actions resulting in a corresponding transition of the at least one agent state; defining a plurality of nodes, each node comprising a system state; and evaluating for a plurality of pairs of nodes, whereby one node of each pair acts as a pre- condition node and the other node of each pair acts as a post-condition node, whether the pair can, given the rules, be directly connected by an edge, each edge comprising an action or actions required for a transition between the respective pre- and post-condition system states.