Autonomous Mobile Robot Action Recommendation From Shared Histories

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Solution Overview

Problem

Existing autonomous mobile robots struggle to efficiently share learning results and improve learning processes, leading to limitations in action planning and movement optimization.

Innovation Solution

An information processing apparatus and method that includes an action recommendation unit, which presents recommended actions to autonomous mobile bodies based on action histories from multiple robots and situation summaries, enabling more informed action planning.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If autonomous mobile bodies perform actions independently based on their own learning, then each body can autonomously execute movements, but learning results cannot be shared with other autonomous mobile bodies

Engineering Contradiction:

Improvelearning capabilityVSAvoidlearning result sharing

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The patent merges the learning systems of multiple autonomous mobile bodies by collecting action histories from multiple bodies and creating a shared learning resource. The action recommendation unit integrates data from multiple sources to generate recommendations that benefit all participating bodies, transforming individual learning into collective learning.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The action recommendation unit serves as an intermediary that receives situation summaries from autonomous mobile bodies, compares them against collected action histories, and generates recommended actions. This intermediary facilitates information exchange and learning sharing without requiring direct peer-to-peer communication between autonomous bodies.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If action plans are made independently without external input, then autonomous mobile bodies maintain operational independence, but the quality and usefulness of action plans are limited

Engineering Contradiction:

Improveoperational independenceVSAvoidaction plan quality

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The system implements feedback by collecting action histories from multiple autonomous mobile bodies and using this accumulated knowledge to generate recommendations. The feedback loop continues as recommended actions are executed and new experiences are added to the collective knowledge base, progressively improving action plan quality while maintaining operational independence.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12204338B2Information processing apparatus, information processing method, and program

Publication Date: 2025.01.21 SONY GROUP CORP

AI summary

There is provided an information processing apparatus and an information processing method that can provide more useful information for an action plan of an autonomous mobile body, the information processing apparatus including an action recommendation unit configured to present a recommended action recommended to an autonomous mobile body, to the autonomous mobile body that performs an action plan based on situation estimation. The action recommendation unit determines the recommended action on the basis of an action history collected from a plurality of the autonomous mobile bodies, and on the basis of a situation summary received from a target autonomous mobile body that is a target of recommendation. The information processing method includes presenting, by a processor, a recommended action recommended to an autonomous mobile body, to the autonomous mobile body that performs an action plan based on situation estimation.