Automatic Obstacle Detection TRIZ Cases

Occupancy-based area segmentation lets a mobile robot distinguish clutter from open zones and follow a user-adjustable coverage sequence.

Pad sensing lets the floor robot identify the attached cleaning pad and automatically choose spraying and navigation modes for effective cleaning.

Sensors classify floor areas so one self-propelled cleaner can vacuum and mop selectively, avoiding wet cleaning on unsuitable surfaces.

A pressure-actuated flap door lets a robot debris bin evacuate efficiently while staying sealed during cleaning and avoiding manual opening.

Orbital pad vibration and a fluid-return path let the robot rewet its pad and scrub dried soil from floors more effectively.

Non-uniform friction from a wire-tilted rotating pad lets the cleaner move in multiple directions while lowering motor load and keeping floor contact.

A pad sensor detects pad features such as spectral marks or RF tags so the robot can choose the right cleaning mode without manual setup.

NFC-based AP transfer lets a robot cleaner connect external terminals securely while reducing setup effort and image exposure risk.

Camera-based user detection lets the robot keep different distances in cleaning and air purification modes to reduce discomfort and collision risk.

A flared bell concentrates sonar pulses into a narrow beam, extending robotic object detection from short-range limits to 9.5 meters.

Multiple bottom optical sensors detect suspension states so a robot vacuum can avoid falls, stop idling, and reduce pollution in tight spaces.

A coaxial cyclonic separator and removable dust bin improve debris separation while making autonomous vacuum maintenance easier.

Multiple images captured under different light modes are combined to remove background noise without motion-induced target image errors.

Magnetically coupled window cleaners detect the initial attachment point and return there after cleaning for safer detachment on high-rise glass.

Multiple pool robots split cleaning, swimmer monitoring, and emergency response tasks to improve pool safety and maintenance coverage.

Debris mapping and learned user patterns let a mobile cleaner target dirty zones, vary suction, and cut battery waste without missing coverage.

Cleaning map and path records let users verify robot cleaner operation remotely while avoiding camera-based security risks.

A detachable mop module separates water storage from the cleaner body to improve wiping area, water capacity, and wet or dry operation.

A wheel-mounted display makes driving direction, power, and obstacle states easier to see while a detachable battery simplifies replacement.

A floor marker and onboard camera let the cleaner learn user-drawn cleaning paths quickly, cutting setup time and unnecessary travel.

A coiled flexible mast forms a conduit around the interface cable, enabling compact sensor lift, tangle prevention, and privacy retraction.

A rectangular front and rounded rear let the robot pivot easily while extending cleaning reach into corners, walls, and tight spaces.

Independent brake units let one wheel stop during steering, reducing wheel wear, motor overheating, and wire tangling in robot cleaners.

By detecting cleaned and uncleaned regions, the robot cleaner avoids overlap and passes narrow entrances to extend coverage efficiently.

Fluorescence sensing guides a mobile UV robot to contaminated surfaces while adjusting dose, distance, and repeat passes to disinfect efficiently.

Acoustic contour sensing lets the robot detect floor changes and adjust movement and cleaning intensity to avoid collisions and clean efficiently.

Optical emitters and a receiver detect bin fill level and debris presence so a cleaning robot can adjust its path and know when collection is full.

Dynamic side-sensor feedback lets a floor-treating robot hold obstacle distance and clean edges accurately across different surface reflectance.

Front wetting, vacuum waste collection, and onboard fluid separation let this autonomous floor robot clean large areas with less labor and contamination.

Location tracking and stored boundary points let an autonomous robot stay within a defined mowing area without wires, improving coverage and safety.

Sector-based partial maps let a robot cleaner use low-cost infrared or supersonic sensors while correcting position errors for full-area cleaning.

A video camera detects edges, slope, and position so a robot vacuum can follow parallel cleaning paths with better navigation accuracy.

Separate dry pickup and wet scrubbing zones let a home robot use fresh fluid and collect waste liquid without recontaminating floors.

Arbitrary-angle rotational travel helps robot cleaners bypass obstacles faster, cut wall-following time, and conserve battery power.

Ceiling-reflected infrared signals let an autonomous robot track position and map obstacles without floor-level interference in cluttered spaces.

Directional and omni receivers work with gateway beacons to let a coverage robot detect room boundaries and switch between cleaning and migration modes.

A docking station uses an agitator comb, vacuum suction, and locking assembly to clear robot roller debris without destabilizing the docked robot.

Caster wheel angle feedback corrects drive wheel slippage, helping a robot cleaner maintain straight travel on carpets and hard floors.

Wireless transponder signals let mobile robots yield to high-priority traffic, avoid collisions, and resume their planned route.

An optical emitter-receiver path inside the sweeper bin detects debris buildup and triggers a bin-full routine to avoid inefficient robot cleaning.

A user-guided virtual perimeter lets an autonomous robot map a closed boundary in memory, avoiding wires while maintaining reliable confinement.

Periodic ultrasonic or infrared mapping detects deviations from stored surroundings and triggers local or wireless alarms.

Compliant flaps, end guards, and a traversing cleaning tool keep pet hair from tightly wrapping robot cleaning rollers and causing jams.

Temporal-spatial data gathered during robot service tasks is reused for 3D mapping, object cataloging, and later localization.

Human-presence sensing lets a service robot pause, move away, or resume work to reduce disturbance while maintaining task efficiency.

Encoded ultrasonic detection triggers wireless guidance signals, helping cleaning robots avoid obstacles, save power, and follow cleaner routes.

Negative-pressure adhesion keeps a window cleaner stable on glass in wind while controlled path movement improves cleaning completeness.

Feature-point particle reprojection lets a single-camera mobile robot build precise 3D maps for better navigation and obstacle avoidance.

Absolute position recognition and image similarity let a robot cleaner resume after a forced stop without re-cleaning finished areas.