Mowers TRIZ Cases

See how a robotic lawnmower adapts its operating schedule by detecting living objects to minimi

See how optical sensors and image comparison replace perimeter wires in autonomous lawn mowers,

See how an autonomous mower washes itself by rotating its work unit to spread tap water across

A single magnetic sensor distinguishes lift from collision by polarity changes, cutting sensor count while improving robotic tool safety.

A sliding seat back adjusts operator support while nesting into a lower profile to cut packaging materials and shipping cost.

A robot follows magnetic field lines from a single base-station coil to cut return time, energy use, and navigation complexity.

A self-propelling robot uses gyroscope-guided magnetic field search and line tracking to return to its base faster with lower system complexity.

Blower drive load is used to detect container fill state without sensors in the airflow path, preserving conveyance efficiency and sensor life.

Elastic crop-contact sensing steers high-stem harvesters into row alignment, reducing manual correction, driver fatigue, and lost time.

By combining target-region and worked-region data, this case shows how operators can track overall field work progress more clearly.

A separable filter mount and suction oil reservoir simplify hydrostatic transaxle filter replacement and reduce manufacturing changes.

Electronic load sensing simulates bog-down in power tools, warning users of overload to prevent damage and reduce battery drain.

A hinged wheel mount shifts wheels beside or behind the towed body to follow ground undulations, work near barriers, and cut towing forces.

A grip lever and slide member unlock the trigger with one hand, preserving grip strength while reducing accidental actuation risk.

A slide rod and bracket linkage raises and holds an angled bubble-up auger without extra locks or actuators, cutting lift system complexity.

In-situ sensing and prior field maps predict changing crop conditions so agricultural machines can adjust control to cut grain loss and stabilize throughput.

Predictive control uses field maps and in-situ data to match harvester auxiliary power demand, reducing deficits, excesses, and wear.

Predefined mode settings let a vehicle controller automatically configure power, header, and lights to avoid manual setup errors.

Field contours and non-work regions are visually segmented on the harvester display to improve recognition inside and outside the field.

Automatic fold and swing control retracts a harvester ladder during transport to reduce vehicle width while restoring cab access in operation.

Distributed handle-mounted displays show drive direction, tilt, and obstacle status in real time to reduce operator fatigue and improve control.

A conductive rear skirt grounds static charge from a metal lawnmower chassis, preventing operator shocks without adding separate discharge hardware.

Tank recesses create tool access to rear-side components in a forage harvester, avoiding tank removal during assembly and maintenance.

A segmented cavity cover keeps water out even when unlocked, simplifying battery pack replacement and eliminating separate waterproof films.

An inverted V ridge supports grain load and adds a non-slip walkway, reducing flow gate wear while keeping wet grain discharge unobstructed.

A combine can rejoin a preset work route from any field position after midway work, reducing manual relocation and improving workability.

Fixed camera positioning and selective data processing give harvester operators clearer, context-relevant views with lower computing load.

Sensor and map-guided entry control lets a working robot leave a transport vehicle and reach the work area without manual carrying.

Dual discharge-permission signals let a power tool block battery discharge when one communication path fails, helping prevent pack deterioration.

An elastomer layer in the cutting disc absorbs knife impacts and vibration, reducing robotic lawn mower noise without losing disc strength.

A helical fuel tank staircase saves space between axles while providing secure, comfortable access to a high harvester cab.

Blade cutting load is used to estimate grass height and adjust mowing time or height without costly grass growth models.

Field contours and non-work regions are mapped from vehicle position data to make combine harvester field status easier to recognize.

Stem thickness sensing estimates incoming crop throughput early, letting a harvester adjust travel speed before overload blocks internal components.

A tension spring and locking plate simplify lawn mower clutch ON-OFF operation while holding stable cutter control without extra locking parts.

Cleanliness thresholds trigger sensor-surface cleaning and confidence control when crop residue blocks agricultural machine signals.

Predictive control adjusts engine-to-unit coupling before load spikes, preventing stalling and improving agricultural machine efficiency.

Disc-shaped wheel segments with uniformly hardened running surfaces improve soil aeration, ground stability, and wear resistance.

Sensor-guided routing evaluates sink region conditions and vehicle weight to avoid paths that would exceed soil compaction limits.

Remote approval and parameter updates help grain carts unload accurately under changing weight, terrain, and fill constraints.

Hierarchical control coordinates charging by battery level, mower location, and base station occupancy to keep multiple robotic mowers working.

Automatic ground-object detection helps turf aerators avoid sprinkler heads by disengaging the implement before contact and re-engaging after passing.

In-situ sensor data and prior soil and topographic maps predict field conditions to keep harvester headers engaged without digging-in.

A cabin-side handrail and movable antenna support let workers reach and reposition a high-mounted antenna without ladders.

Negative motor rotation unlocks the wheel drive clutch during shutdown, avoiding manual wheel turning and reducing part damage.

Selective front caster drive lets a riding mower match rear wheel speed or brake on slopes, improving hill stability and descent control.

A pivot shaft and rotation-limiting axle structure helps vehicles absorb uneven-ground impacts, improve stability, and avoid chassis collision.

A pivoting lever and roller latch secures the battery firmly while reducing friction during removal from power equipment.

Predictive control uses field and machine data to balance harvester power across subsystems, cutting waste, wear, and power deficits.

Longitudinal wheel slip detection triggers an emergency stop in an unmanned tractor to prevent soil damage and simplify field recovery.

A sliding control panel with lock shafts switches between manual and self-propelled modes while enabling variable speed control and safer operation.

Coolant is routed through the inverter, motor, and DC/DC converter in sequence to protect heat-sensitive electronics and stabilize cooling.

A grip lever and slide member unlock the trigger through one-hand gripping, preventing erroneous release without reducing grip strength.

A rear roof-edge receiver layout uses cabin-side bracket space to place the GNSS unit near the swivel center and improve positioning accuracy.

Rear-side cabin mounting places the positioning antenna closer to the swivel center, improving combine harvester field positioning accuracy.

Separate wheel and central suspension assemblies distribute impact loads to keep flex-wing rotary cutters stable during transport.

Sensor feedback adjusts engine speed and hydraulic flow to maintain traction, improve steering response, and cut fuel use at low speeds.

A lithium-ion powerhead uses a horizontal shaft and standard engine support pattern to replace small ICE units with lower emissions.

Two manual switches trigger different motor stop controls, giving electric work machines more flexible deceleration and stopping.

Internal supply and exhaust air ducts let a shaft-mounted tool place its motor more freely while improving cooling, balance, and vibration control.

Visual-inertial fusion combines camera and IMU data to improve mower positioning, mapping, navigation, and obstacle avoidance in complex lawns.

Field images are tied to the robot's self-position to build map coordinates, cutting hardware cost and sustaining autonomous travel in poor reception areas.

Real-time segment-state graphics and field maps help operators raise only affected header sections to avoid bogging and maintain harvest coverage.

Adds vertical position to geofences so vehicle operation can be limited by elevation in multi-level restricted areas.

Heuristic route generation supplies ML training data for agricultural vehicles, cutting field data collection while improving route prediction.

LIDAR, image sensing, and GNSS mapping let mowing vehicles log hidden roadside obstacles and avoid equipment damage during vegetation control.

Boundary-aligned path angles help mowers cut closer to area edges, reducing uncut grass and avoiding extra border passes.

A splined sleeve and locking element let forage harvester feed rollers disconnect from the gearbox for field maintenance without heavy lifting.

Remotely positioned drones monitor header attributes beyond onboard sensor blind spots, improving harvest control accuracy with less machine complexity.

A drone-mounted sensor system avoids debris-obstructed views by planning field travel paths that improve attribute detection accuracy.

Displays a parallel travel line from vehicle position and field edge data so combine auto-steering starts with accurate alignment and fewer readjustments.

Visual sensing classifies woody plants and guides outer-extension traversal so grass under foliage is cut with lower risk of getting stuck.

Dual-pressure hydraulic valve control shifts header float arms between locked and unlocked states to avoid ground contact while preserving cutter bar conformity.

A dual-pressure valve shifts header float arms between locked and unlocked states so the cutter bar follows contours without rutting or header damage.

Prior maps, optical checks, and GPS help harvesters ignore weed-triggered tactile row signals and keep steering aligned in non-crop areas.

A configurable manual override actuator moves a material transfer vehicle by preset distances to correct unloading misalignment quickly.

Gear trains amplify hand torque so power tool implements can be changed without extra tools while a lock mechanism prevents unintended release.

In-situ sensing and field maps predict location-specific power demand, helping harvesters balance performance and energy use.

An override button lets operators correct steering during automatic travel, avoiding manual mode switching while maintaining route control.

A base station and principal mower relay commands to secondary mowers, improving group mowing efficiency and collision avoidance.

Front and proximal cameras correct blade opening offsets in autonomous crop weeding, improving weed removal while avoiding crop damage.

A frame-mounted intermediate pulley reduces deck belt exit angles in compact stand-on ZTR mowers, helping prevent wear and belt failure.

Camera-based fill control guides the receiving vehicle operator on repositioning for uniform loading, reducing spillage during harvesting.

Hierarchical rough, fine, and machine control levels combine remote sensing and live field data to optimize harvest planning with lower complexity.

Threshold-based map updates let a robotic work tool accept small charging station moves automatically, reducing manual reconfirmation time.

A dedicated auxiliary hydraulic circuit adjusts the harvesting implement without starting threshing systems, cutting activation time and energy use.

A slotted arm and cross-member pivot limits arm travel to keep the cutter bar level despite wear, loads, and manufacturing tolerances.

Mounting the GNSS correction terminal in the steering section makes its operating status easy to see from inside and outside the cabin.

Image-based virtual worksite layouts help plan equipment paths and crew tasks more accurately, improving cut quality and field efficiency.

Forward-looking turn detection lets a harvester pre-position its spout during curved travel, reducing spillage and operator intervention.

Aggregated machine, field, and crop data are modeled to initialize harvester settings for specific locations, improving yield and efficiency.

Mapped ineffective areas let a lawn mower cross safe non-grass surfaces, reducing detours and improving mowing coverage and efficiency.

A paired-cable magnetic field guides robot heading for precise docking without boundary-line wear or complex charging station mechanics.

LiDAR and camera data help align a harvester unload conveyor with a receiving vehicle, improving grain transfer accuracy in low-visibility field conditions.

GPS-based path planning selects the least-cost mowing route to fully cover large maintenance areas with lower energy use.

Pre-optimized strategy parameters from similar local contexts let agricultural machines reach better settings faster with less trial-and-error.

Speed-sensor feedback continuously shifts hydraulic motor displacement to maintain torque and drum speed under changing loads on smaller tractors.

In-situ ear size sensing and field maps predict local crop conditions to auto-adjust deck plates, reducing grain loss and MOG intake.

Pitch-angle sensing lets a mower calculate contour-line paths on slopes, reducing remote-control difficulty while keeping travel aligned.

Field sensors and geo-referenced vegetative data are combined during harvesting to qualify predictive models for real-time subsystem control.

In-situ sensing and field maps predict zone-by-zone power demand, helping harvesters allocate subsystem power under changing crop and terrain conditions.

By storing guide-cable magnetic field values near the charger, the mower docks accurately despite cable layout variation and lower system complexity.

Two closely timed images with different exposure settings are processed separately to avoid HDR artifacts and improve obstacle detection.

Adjustable creation-capable field areas help combine harvesters eliminate unworked regions and complete automatic reaping coverage.

Segmented sprocket sections let harvester headers change reel drive diameter quickly without reel disassembly, cutting downtime in the field.

By dividing polygonal lawn maps into sub-regions with reference lines, the controller improves mowing coverage and movement efficiency on complex terrain.

Radar-based vehicle location and grain fill sensing automate conveyor alignment during harvester unloading in dust, darkness, and weak signal conditions.

An optimized UWB beacon layout and AR placement guidance help robotic mowers stay within mapped boundaries when satellite signals are blocked.

Multi-sensor navigation combines odometry, optical surveying, sonar, and IMU data to keep autonomous lawn mowers on course and avoid obstacles.

When GNSS signals are blocked, dead reckoning error correction realigns the robotic work tool to expected positions and trajectories for complete coverage.

A pivotable windrow chute clears access to the transition hood, simplifying tool-free switching between residue processing modes.