Mobile Robot Control Compensating Input Delay Time
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Solution Overview
Problem
Brain-computer interface (BCI) systems experience significant input delay times and errors in analyzing EEG signals, leading to discrepancies between user intentions and robot movements, particularly in mobile robot control applications.
Innovation Solution
A mobile robot control apparatus and method that generates an estimated waypoint map with weighted waypoint vectors based on user EEG inputs, allowing for the determination of a more suitable moving path for the robot by calculating an inner product of the movable path and waypoint vectors, thereby compensating for input delay times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If BCI is used to control mobile robot, then user intention control is improved, but input delay time increases
Solution Approach 1:
The system performs preliminary actions by generating an estimated waypoint map before the delay period ends. The waypoint map estimating unit creates multiple estimated waypoint maps corresponding to different time points during the delay period, allowing the robot to prepare potential paths in advance. When the actual user input arrives, the system can quickly select from pre-computed options rather than calculating from scratch, thereby reducing the effective response delay.
2Loss of information
If EEG analysis is performed to detect user input, then user intention recognition is improved, but measurement precision decreases due to errors
Solution Approach 1:
The system implements feedback by continuously updating the waypoint map estimation based on incoming user inputs. The area target determining unit compares the actual user input with the pre-generated estimated waypoint maps and selects the best matching path. This feedback mechanism allows the system to correct for EEG analysis errors by matching the noisy input against multiple pre-computed possibilities, thereby improving overall measurement precision.
Solution Approach 2:
The system changes parameters by generating multiple estimated waypoint maps with different weighting factors for time points during the delay period. By adjusting the weight given to different time points in the delay period, the system can optimize its response to varying EEG signal qualities and reduce the impact of analysis errors on the final path selection.
3Measurement precision
If multiple time-series user inputs are processed, then path accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the processing task by dividing it into two distinct phases: (1) pre-computation phase where multiple estimated waypoint maps are generated for different time points during the delay period, and (2) selection phase where the best matching path is chosen based on actual user input. This segmentation allows complex processing to be distributed over time, reducing peak computational complexity while maintaining high path determination accuracy.
Data Source
AI summary
Embodiments are directed to a mobile robot control apparatus for compensating an input delay time, which includes: a user input receiving unit configured to receive a user input for moving a mobile robot from an input device; a waypoint map estimating unit configured to generate an estimated waypoint map in which a waypoint vector is defined for each grid, based on the received user input; an area target determining unit configured to calculate a movable path along which the mobile robot is movable from a current position, and to determine a moving path of the mobile robot based on the calculated movable path and the waypoint vector of the estimated waypoint map; and a driving unit configured to move the mobile robot along the determined moving path, and its control method.