Autonomous Navigation Route Evaluation Using Purpose-Based Weighting
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Solution Overview
Problem
Conventional technologies face challenges in determining an optimal travel route for autonomous mobile objects based on specific travel purposes, as they struggle to evaluate and select routes that align with the object's intended goals effectively.
Innovation Solution
An information processing apparatus and system that acquires the travel purpose of a mobile object, sets multiple travel routes, calculates predictive values of travel states for each route, computes evaluation values using weighting values specific to the purpose, and determines the next travel route based on the highest evaluation, enabling the mobile object to autonomously navigate according to its intended purpose.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple travel routes are evaluated based on predictive values and weighting values, then the accuracy of route selection aligned with travel purpose is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system pre-calculates and stores weighting values for different travel purposes (e.g., exploration, rescue, delivery) before actual route selection. When a travel purpose is determined, the corresponding pre-prepared weighting values are directly applied without recalculation, significantly reducing real-time computational complexity while maintaining evaluation accuracy
Solution Approach 2:
The route evaluation process is divided into independent modules: predictive value calculation for each route, weighting value retrieval based on travel purpose, and final evaluation computation. This modular segmentation allows each component to be optimized independently and facilitates parallel processing to reduce overall computational burden
2Adaptability or versatility
If multiple travel routes are set and evaluated in different directions, then the versatility of navigation options is improved, but the time required to determine the optimal route increases
Solution Approach 1:
The system generates multiple travel routes in different directions (excessive action) but only performs full evaluation on the top N routes with highest predictive values (partial action). Routes with sufficiently low predictive values are discarded without complete evaluation, reducing determination time while maintaining the ability to provide diverse navigation options
Solution Approach 2:
The system pre-ranks multiple travel routes based on predictive values calculated from terrain data and mobile object characteristics before the actual route selection process. This preliminary ranking identifies the most promising routes in advance, allowing the system to focus evaluation resources on fewer candidates and significantly reduce the time required to determine the optimal route
Data Source
AI summary
An information processing apparatus includes: a travel purpose acquisition unit that acquires a travel purpose of a mobile object; a setting unit that sets multiple travel routes in different travel directions in a forward area with respect to the mobile object; a calculation unit that calculates, regarding each of the multiple travel routes, a predictive value of a travel state in which the mobile object travels along each of the multiple travel routes; a computing unit that computes, regarding each of the multiple travel routes, an evaluation value for the mobile object to realize traveling according to the travel purpose from weighting values that are predetermined according to the travel purpose and the predictive values; and a determining unit that determines, as a travel route to be followed next, a travel route with the highest evaluation represented by the evaluation value among the multiple travel routes.