Powered Wheelchair Control System for Obstacle Avoidance
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Solution Overview
Problem
Personal mobility vehicles, such as wheelchairs, pose challenges for novice users and even experienced drivers due to the need for complex skills to navigate through environments with obstacles, leading to potential collisions, especially in dynamic and congested spaces.
Innovation Solution
A system that integrates sensors to provide real-time location and structural information, enabling a processing unit to switch between manual and automated control by generating triggers based on obstacle distance and direction, using a grid-based approach to optimize navigation and control the vehicle's speed or acceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated control is used to navigate the personal mobility vehicle, then collision avoidance with obstacles is improved, but the ease of operation deteriorates due to reduced manual control
Solution Approach 1:
The control system dynamically switches between manual and automated modes based on real-time obstacle detection. When obstacles are detected within a threshold distance, the system automatically transitions from manual to automated control mode, and switches back to manual mode when obstacles are beyond the threshold distance, optimizing both safety and user control.
Solution Approach 2:
The system continuously receives feedback from sensors detecting obstacle location and distance information. This feedback loop enables the processing unit to monitor the environment in real-time and adjust the control mode accordingly, switching to automated control when obstacles are detected and returning to manual control when the path is clear.
2Ease of operation
If manual control is provided to the driver, then ease of operation is improved, but the reliability deteriorates due to potential collisions from lack of skill or perception
Solution Approach 1:
The automated control system acts as an intermediary between the manual control inputs and the vehicle movement. When obstacles are detected, the automated system intervenes to override manual control inputs and generate appropriate avoidance maneuvers, ensuring collision prevention while the user retains ultimate control authority.
3Reliability
If the system switches between manual and automated control modes, then collision avoidance is improved, but the device complexity increases due to multiple control mechanisms
Solution Approach 1:
The processing unit serves multiple functions: it processes sensor data for obstacle detection, determines obstacle distance, switches between control modes, and generates automated control inputs. This multi-functionality reduces the need for separate dedicated components for each function, managing system complexity while achieving reliable collision avoidance.
4Reliability
If sensors are used to detect obstacles in real-time, then collision avoidance is improved, but the use of energy increases due to continuous sensing and processing
Solution Approach 1:
The system uses partial sensing action by focusing sensor detection on relevant areas and using threshold-based obstacle distance determination. Instead of continuously processing all sensor data at maximum resolution, the system activates automated control only when obstacles are detected within threshold distances, reducing energy consumption while maintaining effective collision avoidance.
Data Source
AI summary
A system 1 for controlling a powered personal mobility vehicle 8. The system includes an input module 2, a processing unit 4, and a motor controller 7. The input module 2 receives manual triggers 3 regarding the movement of the personal mobility vehicle 8. The processing unit 4 processes a location information 5 or a distance information 6 at a given point in time, and further, either generate an automatic trigger 19, and disable or curtail the functioning of the input module 2, or enable the functioning of the input module 2. The location information 5 is defined as a location of an obstacle co-located in an environment in which the personal mobility vehicle 8 is placed or being driven, and the distance information 6 is defined as the distance of the obstacle from the vehicle 8 at a given point in time. The motor controller 7 receives and processes manual triggers 3 or automatic triggers 19 and controls movement of the personal mobility vehicle 8.