スマートナビゲーションと障害物回避

壁や家具のマッピングだけでなく、カメラやデュアルレーザー、あるいは機械式アームを積極的に活用して、ケーブルや靴、ペットの粗相を識別して避けて通るロボット。

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    Samsung's Jet Bot AI+ combines a 3D sensor with Intel-developed AI to detect household items and avoid them during precision mapping.

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    Xiaomi's X20+ uses LDS laser navigation plus S-Cross structured-light to detect low obstacles even in dim rooms during cleaning.

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    TrueDetect 3D 3.0とTrueMapping 2.0を軸に設計されたコンパクトなOmniドック搭載ロボットで、100平方メートルを約6分でマッピングし、平面的なセンサーシステムでは見逃しがちな低い位置の散らかりを3D障害物検知で識別する。

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    eufy's X10 Pro Omni detects over 100 object types using AI.See obstacle avoidance, handling cables and toys while mapping and mopping.

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    HomeRun series uses cameras and D-ToF laser sensors for autonomous obstacle detection and navigation

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    Multiple models including 360 Vis Nav and Spot+Scrub AI use cameras and LiDAR for precise obstacle recognition

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    iRobot's Roomba Combo j9+ uses on-board camera and AI to recognize and steer around pet waste, cables, shoes, and household clutter during cleaning.

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    LG's CordZero combines LiDAR, RGB camera, and 3D sensor for precise room mapping and obstacle detection along its cleaning route.

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    V12 uses DuoDetect AI 3D obstacle detection with structured light 3D scanning at 5mm accuracy

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    S10 and S20 models use AI-powered cameras to identify 100 obstacle types including cables, socks, and pet waste

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    Dreame's L20 Ultra uses 3D structured-light and AI to recognize about 55 obstacle types, adjusting its cleaning path to avoid them.

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    5軸の折りたたみ式メカニカルアームを搭載した世界初の量産ロボット掃除機。アームを展開して小さな物体や靴下、ケーブル、軽いゴミなどをつまみ、進路の外へ移動させる。21,600以上のデータポイントを持つStarSight 2.0ナビゲーションがこれを支える。

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    RCV 5 combines LiDAR, dual-laser system, and AI camera for precise flat obstacle avoidance

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    Lucy series vacuum uses dual 1080P cameras and depth sensors for AI obstacle avoidance, detecting objects as small as 1 inch

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    Z60 Ultra detects and avoids 200+ object types with dual-laser 3D mapping and RGB camera.

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    Shark's AI Ultra combines 360-degree LiDAR mapping with camera-based NeuroNav obstacle detection to browse around furniture and cords intelligently.

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    360度をスキャンし床すれすれまで監視する3レーザーアレイを軸に設計されており、壁や家具の脚から数ミリの距離まで掃除しつつ、シングルレーザーでは見逃してしまうような低い小さな障害物も捉える。

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    Tapo's RV30 Max Plus combines LiDAR mapping with IMU sensors to browse homes and avoid obstacles like furniture and cords.

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    Proscenicのナビゲーション重視モデルで、8,000Paの吸引力と自動ゴミ排出ステーションに加えてデュアルレーザーシステムによる障害物回避を搭載し、ブランドのエントリーモデルQ10より確実なナビゲーションを求める人向け。

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    バンパーセンサーや平面的なレーザースキャンだけに頼らず、3Dイメージングで前方の物体を視覚的に感知する。靴やペットの餌皿など、日常的な散らかりものにロボットが引っかかってしまうのを防ぐために設計されている。

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    E20 Plus features DuoDetect AI 3D obstacle avoidance using dual-line laser for precise small-object detection

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    X-Plorer 120 AI uses laser and camera tech to detect objects as small as 2 centimeters.

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    Conga 7090 IA features dual cameras and AI to detect and recognize 200+ household objects for obstacle avoidance

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    Matic's robot vacuum uses only RGB cameras and an on-board Nvidia Jetson Orin chip, processing everything locally without relying on LiDAR.

Frequently asked questions

How do these robots handle small objects like cables or socks?

Many models use AI cameras and 3D sensors to recognize and steer around these items. Some advanced options even feature a mechanical arm that can pick up small objects like socks and cables to move them out of the cleaning path.

Can these vacuums navigate effectively in dark rooms?

Yes. Certain models use structured light technology to detect low obstacles even when lighting is dim. Others combine LiDAR with cameras to maintain precise mapping and navigation.

What kind of objects can the AI actually identify?

High-end models can recognize over 100 different object types, including pet waste, shoes, and toys. This allows them to adjust their cleaning paths to avoid specific types of household clutter.

How do the sensors work to prevent collisions?

These robots use a variety of technologies such as 3D scanning, LiDAR, and RGB cameras. Some use structured light with high accuracy to identify low-lying obstacles that standard mapping might miss.