Mowers TRIZ Cases

Automatic detection of attached work machine state updates autonomous travel settings, avoiding manual retuning and mismatched work.

Independent header segments use actuator control to follow field contours and keep cutting height consistent while the harvester stays mobile.

Phase-difference and signal-strength sensing let a robotic mower map its area and avoid random, repetitive paths without complex infrastructure.

Automatic detection of attached work machines updates autonomous travel settings, avoiding manual readjustment after tool replacement.

A mobile approval app verifies operator proximity and machine readiness before autonomous motion, reducing startup errors and damage.

Direction-dependent damping lets a belt tensioner absorb torque reversals through controlled slippage, reducing belt and drivetrain wear.

A dual-input differential keeps axle rotation active when the main drive path fails, reducing wheel slip and stabilizing movement transfer.

Context sensing uses GPS, cameras, and operator input to suppress false row signals, preventing unwanted harvester steering in non-crop areas.

An auxiliary input path keeps the output gear rotating when main meshing fails, reducing wheel slip and stabilizing movable power tools.

Recorded track paths, drier-area routing, and windrow offset control help farm machines limit soil compaction and stand damage.

Automatic route correction shifts adjacent reaping courses together, reducing manual adjustments and preventing missed cereal rows.

Multiple cameras capture crop and machine position states for faster harvesting control with less manual intervention in unmanned operation.

When GNSS positioning degrades, fused dead reckoning and boundary distance calculations trigger safety actions before the mower breaches its work area.

Rotational-speed-actuated weights engage a central shaft inside the disk perimeter, enabling automatic clutching with less space and no user input.

A laterally deformable linkage and vertical sliding shaft let the machine distinguish obstacle hits from lifting and avoid false stops.

Cross-connected hydraulic motors and pumps prevent roller segment slippage and fluid loss without flow dividers, improving energy use.

RTK-style correction data lets a mobile device define precise virtual mowing boundaries, avoiding drift that causes missed or unintended cutting.

Cross-connected hydraulic motors and pumps curb roller-segment slippage and fluid loss while maintaining torque and speed in soil tillage machines.

Creates forward or backward discharge and return routes so a combine harvester can transfer efficiently between work, discharge, and return positions.

A two-stage lock member and trigger lever simplify power-on in handheld cutting tools while maintaining a safety interlock.

In-situ sensing and field maps predict crop variation so harvesters can auto-adjust settings, improving efficiency and reducing crop loss.

Combining in-situ sensor data with field maps lets harvesters predict biomass changes ahead and adjust settings for higher throughput.

In-situ sensing and field maps predict local power demand so harvesters can adjust control settings across dense crops, weeds, and moisture changes.

When common-view satellites drop, the mower switches RTK base stations using trajectory alignment to maintain accurate positioning near buildings.

Preplanned turn paths keep the support vehicle aligned with the harvester during field turns, enabling continuous unloading and reducing crop loss.

A solar-powered laser boundary limits tree and shrub growth by causing localized tissue necrosis, reducing trimming and chemical use.

A locking element and integrated actuator secure garden machine blades under dynamic loads while enabling safe, toolless removal.

A preset recharging path guides the mowing robot into charging alignment while avoiding repeated rotation points that damage turf.

A guide portion and movable U-shaped pin simplify heavy attachment alignment and locking, cutting pin insertion time while keeping retention secure.

Route planning sets workload-based interruption points and detours around unreaped areas so a self-driving combine can perform mid-work smoothly.

In-situ sensor data and field maps predict weed intensity ahead of harvest, enabling machine control that avoids slowdowns and damage.

Removable battery packs and controller-based switching keep an autonomous lawn mower running longer without recharge downtime or supervision.

Triangular mesh decomposition and longest funnel-path planning cut traversal time and energy while ensuring complete area coverage.

In-situ sensor data and field characteristic maps are combined to predict location-based machine settings for more precise automated farm control.

Dynamic steering angle limits help autonomous work vehicles stay between crop rows, reducing crop contact while maintaining stable path tracking.

A dedicated safety controller handles self-checking in a dual-control self-moving machine, improving reliability without slowing operation.

Periodic motor and blade noise is identified across sensor readings and subtracted to preserve fast, accurate robotic mower navigation.

A self-aligning bearing between fan and motor hubs compensates for shaft misalignment, cutting vibration, noise, and premature wear.

A user-verified boundary run corrects mower map errors before autonomous cutting, improving coverage and preventing unsafe area entry.

Location-based laser curtain patterns help autonomous crop row vehicles avoid collisions while reducing manual labor in field operations.

A self-actuating pin lock lets the header arm switch cutter bar modes faster by removing manual pin alignment and heavy arm handling.

A movable dual-pulley tensioner raises belt tension in reverse for obstruction clearing and lowers it in forward drive to extend belt life.

Field boundaries are segmented into headland and work polygons so replicated seed tracks can guide autonomous turns with less crop damage.

Stereo vision, GNSS, IMU, and stored elevation data are combined to separate crop canopy from ground and improve harvester yield estimates on slopes.

In-situ sensing and field maps forecast local yield shifts so harvesters can adjust settings early and avoid grain loss or plugging.

Variable speed on edge-side turning routes keeps an autonomous combine inside field boundaries without stopping for manual intervention.

When a charging station is moved slightly, the robot updates its stored map automatically to keep navigation and docking accurate without manual confirmation.

UWB ranging, image features, and IMU motion estimates define robot service-area boundaries more accurately than contact-based methods.

When positioning becomes uncertain, the mower uses dead reckoning and a dynamic navigation margin to stay within the boundary.

Placing the correction-status display in the steering section makes GNSS receiver state easy to check without interfering with vehicle operation.