Adaptive Trajectory Controller for Autonomous Lawn Mower Realignment
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Solution Overview
Problem
Autonomous systems, such as lawn mowers, often divert from their intended trajectories due to environmental conditions, sensor errors, or component inconsistencies, requiring frequent recalculations of trajectories, which consumes substantial resources and time.
Innovation Solution
The implementation of a controller with kinematics and dynamic components that monitor the system's current state and generate adjustment signals to return the system to the target trajectory without necessarily recalculating the entire trajectory.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system recalculates the trajectory multiple times to correct deviations, then the system can return to the target trajectory, but substantial computational resources and time are consumed
Solution Approach 1:
The controller is divided into distinct functional components: a kinematics component that handles trajectory deviation detection and compensation calculation, and a dynamic component that executes control signals. This segmentation allows the system to address trajectory corrections through localized computational tasks rather than full trajectory recalculations, reducing overall computational burden and time consumption.
Solution Approach 2:
The kinematics component continuously monitors the current state and compares it with the target trajectory in advance, calculating compensation values before significant deviations occur. This preliminary detection and compensation approach prevents the need for reactive full recalculations, thereby saving computational resources and time while maintaining trajectory accuracy.
2Reliability
If the system recalculates the trajectory multiple times to correct deviations, then the system can return to the target trajectory, but substantial computational resources are consumed
Solution Approach 1:
By segmenting the control system into kinematics and dynamic components, the computationally intensive task of full trajectory recalibration is avoided. Instead, the kinematics component performs lighter computational operations to calculate compensation values based on current state deviations, significantly reducing energy consumption while maintaining trajectory accuracy.
Solution Approach 2:
The system applies partial correction actions through compensation values calculated by the kinematics component, rather than performing complete trajectory recalculations. This partial action approach addresses only the specific deviation from the target trajectory, consuming fewer computational resources and energy while achieving the necessary correction.
3Stability of the object's composition
If the controller continuously monitors and adjusts the system state, then the system maintains stability on the target trajectory, but the device complexity increases
Solution Approach 1:
The controller is segmented into a kinematics component responsible for state monitoring and compensation calculation, and a dynamic component responsible for executing control signals. This segmentation organizes the complexity into manageable, functionally distinct modules, making the overall system easier to implement and maintain while ensuring continuous stability through dedicated monitoring and adjustment functions.
Data Source
AI summary
Techniques and architectures for controlling movement of a system along a desired path in an efficient manner are discussed herein. For example, an autonomous lawn mower can be configured to determine a target state for the autonomous lawn mower indicating a target position, orientation, linear velocity, rotational velocity, etc. The autonomous lawn mower can determine a difference between a current state of the autonomous lawn mower and the target state. Based on the difference, the autonomous lawn mower can determine an amount of force/torque and control the autonomous lawn mower to move based on the amount of force/torque, which can cause the autonomous lawn mower to realign with a target state.