Autonomous Mobile Object Behavior Planning with Opposing Needs
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Solution Overview
Problem
Autonomous mobile objects exhibit simplistic operation patterns when behaviors are determined based on estimated circumstances, leading to decreased user interest due to uniformity and lack of natural interaction.
Innovation Solution
An information processing apparatus with a behavior planner that determines behaviors for autonomous mobile objects based on estimated circumstances and multiple sets of opposing needs, such as self-preservation and self-esteem, allowing for more natural and flexible behavior plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If behaviors are determined based on estimated circumstances alone, then the autonomous mobile object can execute operations according to a behavior plan, but the operations become simplistic and uniform, leading to decreased user interest
Solution Approach 1:
The behavior determination process is segmented into multiple independent components: circumstance estimation, need identification (self-preservation and self-esteem needs), and integrated behavior selection. This segmentation allows each component to be processed separately and combined to create more nuanced behavior plans that avoid simplistic uniform responses.
Solution Approach 2:
The system dynamically adjusts behavior determination by considering the relative importance of different needs (self-preservation vs. self-esteem) based on current circumstances. The behavior plan is not static but adapts in real-time by weighing multiple opposing needs, enabling flexible and natural-looking operations that maintain user interest.
2Productivity
If uniform behaviors are determined for estimated circumstances, then the behavior plan can be executed systematically, but the autonomous mobile object exhibits simplistic operation patterns, reducing user interest
Solution Approach 1:
The system changes the parameters of behavior determination by introducing multiple need dimensions (self-preservation need degree and self-esteem need degree) instead of relying solely on circumstance estimation. This multi-parameter approach allows the same circumstance to produce different behaviors based on the relative importance assigned to different needs, thereby diversifying operation patterns while maintaining systematic execution.
Solution Approach 2:
The behavior plan is constructed as a composite of multiple need assessments rather than a single circumstance-based determination. By combining self-preservation needs and self-esteem needs in a unified decision-making framework, the system creates rich, diverse behavior patterns that maintain both execution efficiency and operational diversity.
3Adaptability or versatility
If multiple sets of opposing needs are considered in behavior determination, then more natural and flexible behavior plans can be implemented, but the complexity of the behavior planner increases
Solution Approach 1:
The behavior planner employs a self-service mechanism where the autonomous mobile object autonomously evaluates its own needs (self-preservation and self-esteem) based on current circumstances and automatically determines appropriate behaviors. This self-service approach manages complexity by eliminating the need for external control systems while maintaining flexible, natural-looking behavior through internal need assessment and resolution.
Data Source
AI summary
There is provided an information processing apparatus and information processing method to implement a more natural and flexible behavior plan of an autonomous mobile object, the information processing apparatus including a behavior planner configured to plan a behavior of an autonomous mobile object based on estimation of circumstances, wherein the behavior planner is configured to, based on the circumstances that are estimated and multiple sets of needs that are opposed to each other, determine the behavior to be executed by the autonomous mobile object. The information processing method includes, by a processor, planning a behavior of an autonomous mobile object based on estimation of circumstances, wherein the planning includes, based on the circumstances that are estimated and multiple sets of needs that are opposed to each other, determining the behavior to be executed by the autonomous mobile object.


