Vehicle Cabin Motion Planning for Custom Seating Reconfiguration
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Solution Overview
Problem
Current motion planning of vehicle cabin transitions is manual and inefficient, requiring unnecessary intermediate steps and increasing transition time, and there is a need for automated path planning that allows users to create custom modes without additional inconvenience.
Innovation Solution
A system that automates path finding by modeling cabin configurations as nodes in a network, using a controller to determine optimal transition sequences based on transition time and movement counts, and employs actuators to move interior components according to these sequences, eliminating potential interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual motion planning is used for cabin transitions, then the system is simple to implement, but transition time increases and efficiency decreases
Solution Approach 1:
The system performs automated motion planning independently without requiring manual intervention. The controller automatically generates transition sequences, calculates cost values, and executes cabin reconfiguration based on the selected mode, making the system self-sufficient in optimizing transition paths
Solution Approach 2:
The system changes the planning approach from manual fixed sequences to automated dynamic sequencing based on cost value calculations. By evaluating multiple transition sequences and selecting the one with the lowest cost value, the system optimizes transition parameters automatically
2Loss of time
If traditional transition sequences are used, then the control logic is simple, but unnecessary intermediate steps increase transition time
Solution Approach 1:
The system pre-calculates and stores multiple transition sequences between cabin modes along with their cost values. When a transition is needed, the controller retrieves pre-planned sequences and selects the optimal one, avoiding real-time computation delays
Solution Approach 2:
The automated path planning algorithm identifies and executes the most direct transition sequence by comparing cost values, effectively skipping unnecessary intermediate steps that would be included in traditional fixed transition protocols
3Adaptability or versatility
If user-defined custom modes are implemented, then adaptability increases, but system complexity increases
Solution Approach 1:
The controller uses a universal motion planning algorithm that can handle both manufacturer-defined and user-defined cabin modes. The same automated path planning and cost value calculation mechanisms work for all mode types, making the system multi-functional without requiring separate control logic
4Productivity
If automated motion planning with cost value optimization is implemented, then transition efficiency improves, but computational requirements increase
Solution Approach 1:
The system pre-calculates and stores cost values for multiple transition sequences between cabin modes during system initialization or mode definition. This preliminary computation avoids repeated real-time calculations during actual transitions, reducing computational energy consumption
Solution Approach 2:
The system uses stored transition sequences and cost value data as templates for automated planning. Instead of performing complex real-time optimization, the controller retrieves and selects from pre-computed sequence copies, significantly reducing computational requirements
Data Source
AI summary
A system for controlling a reconfigurable seating arrangement in a vehicle includes memory storing a plurality of cabin modes including a predetermined location and configuration for each of a plurality of moveable interior components, each stored as nodes in a network model. The nodes are connected by edges extending between ones of the nodes selected as possible successive cabin modes with associated edge cost values. A controller receives a selected one of the plurality of cabin modes and determines a first transition sequence between a current one of the cabin modes and the selected cabin mode by identifying a first one of the nodes that corresponds with the current cabin mode and a second one of the nodes that corresponds with the selected cabin mode. The controller moves at least one of the moveable interior components according to the first transition sequence.