Interactive user applications for remotely communicating with and training autonomous laundry systems
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Solution Overview
Problem
Current laundry systems, including both home appliances and laundromats, are inefficient and costly due to the need for human intervention, leading to delays, inconsistent results, and potential contamination risks, while also wasting resources like water and energy with each load processed.
Innovation Solution
An autonomous robotic laundry system that includes networked devices for real-time communication and control, allowing for the automated sorting, washing, drying, folding, and packing of laundry without human contact, using sensors and machine learning models to optimize processing based on user preferences and article characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If laundry processing is outsourced to laundromats with human operators, then laundry can be cleaned, but human intervention causes delays, contamination risks, and increased costs
Solution Approach 1:
The system enables self-service through autonomous robotic devices that independently sort, wash, dry, fold, and pack laundry without human intervention. The robotic sorters automatically categorize items, and the entire process is managed by control systems that coordinate multiple devices, eliminating the need for human operators while maintaining cleaning quality and preventing contamination.
Solution Approach 2:
Manual mechanical operations by human workers are replaced with automated robotic systems. Robotic arms with sensors detect and sort laundry items, automated washers and dryers process the loads, and robotic folders fold and pack the cleaned items. This substitution of human mechanical action with automated mechanical systems eliminates contamination risks while preserving laundry cleaning effectiveness.
2Reliability
If traditional home washing machines are used, then laundry can be washed, but sequential processing of single loads limits efficiency and increases time consumption
Solution Approach 1:
The laundry system is divided into separate functional modules: robotic sorters, washers, dryers, folders, and packers that operate independently but are coordinated by a central control system. This segmentation allows different stages of laundry processing to occur simultaneously rather than sequentially, dramatically increasing productivity while maintaining reliable washing and drying functions.
Solution Approach 2:
The system maintains continuous operation by having multiple devices work in parallel on different laundry loads simultaneously. While one load is being washed, another can be dried, and a third sorted, eliminating idle time between sequential operations. The control system ensures seamless transitions and continuous productive action across the entire laundry processing workflow.
3Ease of operation
If laundromat services are used for residential laundry, then laundry processing can be outsourced, but human-dependent processes increase operational costs and energy consumption
Solution Approach 1:
The system provides automated self-service laundry processing that eliminates the need for human workers at laundromats. Users can initiate laundry processing remotely through a computing device, and the autonomous robotic system handles sorting, washing, drying, folding, and packing automatically. This maintains the convenience of outsourcing laundry while eliminating the energy waste associated with human-operated facilities.
Solution Approach 2:
The control system continuously monitors and optimizes energy consumption across all laundry processing devices. Sensors detect the state of each load and adjust operating parameters in real-time to minimize energy usage while maintaining processing quality. The system learns from operational data to improve efficiency over time, reducing energy consumption per load compared to traditional laundromat operations.
Data Source
AI summary
Devices, systems, and methods for communicating between remote users and a system of autonomous robotic devices for processing residential loads of laundry are described. An autonomous robotic laundry system includes plurality of robotic devices configured to process one or more loads of household laundry from a mass of unwashed, non-uniform articles to individually separated, cleaned, folded, and packed laundry articles. In implementations, the autonomous robotic devices are configured to operate based on optional inputs communicated by a device of a remote user to at least one controller in operable communication with the autonomous robotic devices. The robotic devices are configured to determine how to process the deformable laundry articles based on at least one of applying sensor output to a machine learning model and executing routines incorporating the optional inputs. The at least one controller is configured to provide real-time updates of two or more process statuses of the system.