Intelligent cabinet type dish washing machine with visual identification and automatic grabbing and storage functions

Abstract

The invention discloses an intelligent cabinet type dish washing machine with visual recognition and automatic grabbing and storage functions, and belongs to the field of intelligent kitchen household appliances. Comprising a cabinet body, a cabinet door capable of being turned into a tray, a folding mechanical arm, visual identification, a space algorithm, AI interaction, cloud communication and an integrated storage cabinet. A user places tableware disorderly, the system performs automatic identification, actuarial space and mechanical arm stacking; automatic temporary storage prompting is carried out on excessive / unsuitable tableware; after washing, automatic storage is carried out according to habits; and batch continuous washing, voice interaction, user habit learning and data cloud iteration are supported. Full-process automation is achieved, the space utilization rate and cleaning safety are improved, manual operation is reduced, through AI and cloud continuous optimization, user stickiness is enhanced, and the method is suitable for family and commercial scenes.

Description

Technical Field

[0001] This invention belongs to the field of smart kitchen appliances, specifically relating to a cabinet dishwasher and tableware storage device that integrates visual recognition, spatial algorithms, automatic grabbing and stacking, AI interaction and cloud iteration. Background Technology

[0002] Traditional cabinet dishwashers rely on manual placement of dishes, which has the following technical drawbacks: 1) Manual stacking is inefficient, has poor space utilization, and limits the amount that can be loaded at one time; 2) Improper placement density and angle can easily lead to incomplete cleaning or damage to tableware due to collision; 3) It cannot automatically identify materials and sizes; it is not heat-resistant; and oversized tableware is easily damaged. 4) After cleaning, it needs to be manually removed and put back in its place, which is a cumbersome operation; 5) Lack of user habit learning, voice interaction and data iteration capabilities, resulting in low user stickiness. Existing technologies have not achieved a closed-loop process of "visual recognition - spatial calculation - automatic grasping - cleaning - automatic storage - batch washing - AI learning - cloud iteration", and cannot meet the needs of efficient, safe, intelligent and personalized use. Summary of the Invention

[0003] 3.1 Technical problems to be solved This invention aims to solve the following problems: inefficiency of manual stacking, waste of space, uncontrollable cleaning effect, fragile tableware, inability to identify incompatible materials, cumbersome repositioning, lack of intelligent learning and iteration, and insufficient user stickiness. 3.2. Technical Solution and Operation Procedure This solution achieves fully automatic intelligent washing and storage through the following steps: 1. Structural preparation stage (see...) Figure 1 ): When the device is in standby mode, the robotic arm folds and retracts into the storage slots on both sides of the cabinet door, flush with the overall appearance of the machine. The cabinet door is closed, and the washing compartment is sealed. 2. Identification and Actuarial Stage (see...) Figure 2 , Figure 3 ): The user opens the cabinet door, causing it to flip downwards 90° to form a horizontal tray. The dishes to be washed are then placed haphazardly on the tray. The top visual recognition module collects image information in real time and transmits it to the central control unit. The algorithm within the unit automatically identifies the type, size, material, and quantity of tableware, and combines this with the internal space data of the washing chamber to generate the optimal grabbing order and internal stacking scheme through a space optimization algorithm. 3. Automatic grasping and stacking stage (see...) Figure 2 ): The robotic arm extends from the storage tank and precisely grabs the tableware from top to bottom according to the planned scheme, placing them one by one into the shelf in the washing chamber. If unsuitable tableware is identified (such as heat-sensitive plastic), or if the number of identified items exceeds the single-use capacity, the robotic arm will grab the items and place them in the temporary storage area, while simultaneously triggering an alarm from the voice prompt unit. 4. Cleaning and storage stage (see...) Figure 3 ): Once the tableware is loaded and the cabinet door is closed, the dishwasher will begin its high-temperature washing program. After washing, the cabinet door opens automatically. The robotic arm extends again, grabs the dishes one by one from the washing chamber, and accurately places them in the designated positions in the dish storage cabinet according to the user's usage habits. 5. Batch processing and intelligent iteration stage (see...) Figure 3 , Figure 4 ): The robotic arm automatically transports the tableware in the temporary storage area for a second batch of cleaning and storage. All data is recorded by the central control unit. The AI ​​interaction module analyzes user voice feedback (such as "a certain area is not clean") and uploads the usage data to the server via the cloud communication module. The detergent monitoring module monitors the detergent level in real time and reminds the user to replenish it via voice prompts and push notifications to mobile devices when it is low. 3.3 Beneficial Effects 1) Fully automated and unmanned: Eliminates the need for manual stacking and returning, reducing operational burden; 2) Maximize space utilization: precise algorithm calculations simultaneously improve loading rate and cleanliness; 3) Safety protection: Automatically identifies dishes that are not suitable for washing, preventing deformation and breakage due to high temperatures; 4) Batch processing: Automatic temporary storage and subsequent washing of excess volume to improve processing capacity; 5) AI Personalization: Learns user habits and adapts for optimization; 6) Data-driven iteration: Cloud-based collaboration, continuous upgrades, and enhanced user engagement. 4. Description of the attached drawings Figure 1 Overall 3D structure diagram Figure 2 Working status diagram Figure 3 System control block diagram Figure 4 Enlarged view of the robotic arm structure 5. Detailed Implementation 5.1 Hardware Components - Cabinet: Integrated washing chamber, heating pump, spray system, and drainage system; - Cabinet door: 90° downward tilt limit, built-in force support and anti-slip structure; - Robotic arm: multi-degree of freedom, flexible gripping, folding and storing in the side groove of the cabinet door, and remaining flush when stationary; - Vision module: Top high-resolution camera + depth sensor, equipped with supplemental lighting and anti-water fog components; - Control unit: main control chip + spatial planning algorithm + material recognition model; - AI Interaction: Speech recognition, semantic understanding, user preference database, self-learning strategies; - Storage cabinet: integrated top, partitioned positioning, supports habitual storage; - Communication: WiFi / Bluetooth, connecting the cloud and user terminals; - Monitoring: Detergent, water softener salt, and rinse aid level sensors. 5.2 Workflow (see...) Figure 3 ) 1) Users open the cabinet door to form a tray and place the dishes to be washed in an disorderly manner; 2) Visual recognition is initiated to complete the detection of type / size / material / quantity; 3) The algorithm outputs the optimal placement position and orientation; 4) The robotic arm grabs and puts the dishes into the chamber; excess / unsuitable dishes are moved to temporary storage and a notification is given; 5) Close the door and start the washing program; 6) The cabinet door will open automatically after washing is complete; 7) The robotic arm returns to its usual position in the storage cabinet; 8) Automatically load temporarily stored tableware for further washing and return it to its original position; 9) Complete voice prompts; local and terminal reminders for insufficient auxiliary materials; 10) User voice feedback is recorded and iterated upon by the system; 11) Use encrypted data to upload to the cloud to support product development. 5.3 AI Learning and Cloud Iteration The system establishes user profiles, recording placement preferences, prohibited materials, cleaning intensity, and return locations; it reviews and optimizes before each execution; and it anonymizes the data and uploads it to the cloud for algorithm iteration, structural optimization, and function upgrades, thereby fostering long-term user engagement.

Claims

1. A smart cabinet-style dishwasher with visual recognition and automatic grasping and storage, characterized in that, include: Cabinet, washing chamber, cabinet door that can be flipped down 90° to form a tray, foldable multi-degree-of-freedom robotic arms set in storage slots on both sides of the cabinet door, top visual recognition module, central control unit, AI interaction module, cloud communication module, top integrated tableware storage cabinet, auxiliary material monitoring module, voice prompt and mobile terminal push unit; The visual recognition module is used to identify the type, size, material, and quantity of tableware; the central control unit has a built-in space optimization algorithm that generates the optimal stacking scheme by combining the three-dimensional parameters of the washing chamber; the robotic arm is used to automatically grab, stack, and return tableware to its position; excess or unsuitable tableware is automatically transferred to the temporary storage area and a prompt is given; after washing, the tableware is automatically stored according to the user's habits; batch washing, AI learning, and cloud iteration are supported.

2. The dishwasher according to claim 1, characterized in that, The cabinet door flips down 90° to form a load-bearing plane, and the robotic arm is folded and stored in the slots on both sides of the cabinet door, so that it is flush with the appearance when at rest.

3. The dishwasher according to claim 1, characterized in that, The visual recognition module includes a camera, a depth sensor, and an anti-water fog supplementary lighting component, enabling rapid identification and positioning of disordered tableware.

4. The dishwasher according to claim 1, characterized in that, The central control unit performs spatial calculations to determine the angle, position, and order of tableware placement, ensuring cleaning effectiveness and loading rate.

5. The dishwasher according to claim 1, characterized in that, The robotic arm uses flexible grippers to hold the object from top to bottom, avoiding collisions and drops.

6. The dishwasher according to claim 1, characterized in that, The system automatically identifies items that are not heat-resistant or are oversized, making them unsuitable for washing dishes, and transfers them to a temporary storage area through the auxiliary material monitoring module; or it identifies that the consumables are running low and provides prompts through the voice prompt unit and the mobile terminal push unit.

7. The dishwasher according to claim 1, characterized in that, After washing, the door opens automatically, and the robotic arm returns the tableware to the tableware storage cabinet according to the user's habits.

8. The dishwasher according to claim 1, characterized in that, Supports multiple batches of continuous washing: The tableware is temporarily stored in the temporary storage area, and the robotic arm automatically washes and returns it to its original position, without any human intervention.

9. The dishwasher according to claim 1, characterized in that, The AI ​​interaction module supports voice feedback, question recording, and preference learning, and will adaptively optimize for the next execution.

10. The dishwasher according to claim 1, characterized in that, The cloud communication module will upload user data in anonymized form for product iteration and optimization, thereby improving user engagement.

Images