Vehicle Position/Course/Altitude Control TRIZ Cases

On-board obstacle detection and route replanning let underground mining vehicles bypass loose rock without manual intervention or stoppages.

Wireless group control replaces string links between vehicles, enabling flexible formation changes without stopping for reconnection.

Reinforcement learning backstepping helps unmanned vehicle formations stay stable despite actuator faults and sensor deception attacks.

Convex sub-area routing reduces repeated turns in narrow mowing sections, improving coverage efficiency and cutting operation time.

A 3D sensor predicts lateral slope ahead of a harvester, enabling proactive self-levelling to reduce rollover risk and tree damage.

Filtered barometric and geolocation data improve UAV altitude change detection, enabling steadier 3D position control in disturbed conditions.

Adaptive LiDAR control changes vertical FOV and transmit power by driving status to cut ground blind spots and avoid wasted power.

Two preliminary tower images are used to generate ellipse-based drone paths, reducing manual piloting while improving photogrammetric accuracy.

Dynamic risk scoring reallocates robots to remote operators, balancing oversight load, tele-operation response, and safe autonomous operation.

Distance and posture data gathered during corner turns let a pool cleaner predict one precise rotation angle and avoid wall collisions.

Layered costmaps combine static, dynamic, and historical traffic data to plan collision-avoiding paths for mobile objects in complex navigation areas.

UWB anchors and a UAV tag enable precise autonomous landing through multi-zone descent control, reducing weather and visibility dependence.

Predefined maneuvering areas and connecting lanes split yard transport into local maneuvers and fixed-route travel for safer, more reliable automation.

Dynamic control timing switches between fixed, shorter, and on-demand cycles to cut unmanned vehicle response delays and collision risk.

Bounded optimization infers initial aircraft mass from observed altitude profiles by replacing tabular segments with throttle laws for better trajectory and fuel-burn analysis.

Guidance logic adjusts airspeed, altitude, or heading to preserve line of sight to a target when fixed flight paths would enter occlusion regions.

Real-time visual and wireless indication signals let robots adjust paths in changing environments and reach destinations accurately.

Roof-mounted accessories with antennas and computing guide drone landing, takeoff, relay messaging, and charging to ease delivery deployment barriers.

Distance sensing and IMU posture data let a pool cleaner calculate turn angles at non-right corners, reducing wall hits and improving mapping.

UWB ranging triggered over Bluetooth lets autonomous mobile devices detect intruders beyond sensor blind spots and adjust paths before collisions.

Pre-takeoff NADP parameter entry in the FMS automates airport-specific departure procedures, reducing pilot workload and human error.

Position-based depot rules let vehicles choose flexible paths while activating or restricting onboard functions for safer, more efficient movement.

Precomputed return positions and route guidance help remote operators steer mobile machines back to autonomous paths after obstacle avoidance.

Direct plan and cost exchange lets unmanned vehicles resolve likely conflicts without UTM dependence, reducing collision risk in shared airspace.

Pre-takeoff NADP input pages let pilots set airport-specific altitude, speed, and thrust values for automated FMS execution and lower workload.

Dummy wall plates let an AMR localize accurately near work robots, enabling precise workpiece transport without rails or floor guides.

Mobile electric chassis with onboard navigation replace fixed conveyors, enabling flexible vehicle final assembly with easier line changes and expansion.

Monocular vision triangulates tree emergence and shake points, enabling precise orchard navigation and lower fruit and tree damage.

Tracks people and obstacles, predicts movement, and updates cost maps so robots navigate crowded spaces safely and smoothly.

Posture sensing and input correction align operator intent with mobile body movement, making remote control more intuitive and accurate.

A taught boundary and environment map let the robot generate a maximum cleaning region, reducing overlap and missed areas in complex spaces.

Drones with onboard sensors detect ride reach-envelope overlaps faster and more accurately than manual attraction interference checks.

Automatic switching between primary and secondary autopilots with backup aviation sensors keeps UAV flight stable after controller failure.

By converting onboard 3D LIDAR scans into 2D images, transit vehicles can localize accurately without heavy computing or wayside equipment.

User position tracking and trajectory analysis let a self-moving waste container relocate for convenient disposal without disrupting daily activity.

Tilted walls and lens-guided light paths isolate multiple light sources in a navigation optical engine, improving surface identification accuracy.

UV-illuminated alignment strips help AGVs follow durable floor guidance when painted lines fade, distort, or become hidden.

A robot cleaner detects movable objects, shifts them aside to clean blocked areas, and returns them after cleaning for full coverage.

Multi-angle guide-sensor scanning helps AGVs quickly reconnect to damaged path guides, stabilizing turns and intersections with less delay.

Tag reading links each cart or load to category-based destinations, improving sorting efficiency and storage placement without manual handling.

Worksite map analysis detects obstructed physical markers and generates resolutions to keep mobile machine localization and navigation accurate.

Dynamic zone policies adjust warehouse vehicle speed from sensor-detected location and hazards, improving safety without constant slowdowns.

Confidence-rated DSM updates let UAVs vary terrain clearance by grid cell, reducing collision risk without shrinking usable airspace.

Cross-checking encoder and environment-sensor vectors enables safety-oriented speed monitoring for omnidirectional mobile units without extra hardware.

Cloud processing and drift correction help drone LIDAR reconstruct 3D targets in near real time while limiting battery use and GPS error.

Captured images let users choose robot movement destinations visually, avoiding manual location entry and improving selection accuracy.

Sensor-based omission detection records missed coordinates and replans mower paths to correct GPS or terrain-driven coverage gaps.

Selective anti-incursion logic follows the planned taxi path to avoid spurious alerts and unnecessary braking during aircraft ground movement.

A handheld remote lets wing walkers stop or resume an aircraft tug directly, avoiding communication delays that can cause ground collisions.

When a cleaning robot gets stuck at floor transitions, it detects surface attributes and re-enters from a different direction to avoid re-trapping.

Separate AM and FM processing in FMCW LiDAR speeds range and velocity measurement while reducing short-range aliasing.

A 4D ellipsoid model turns coupled thrust and torque limits into a normalized maneuvering reserve that pilots can read and use safely.

By adjusting landing points and center of pressure in real time, this case improves legged robot stability against unknown disturbances.

Leader robots assign following road segments so warehouse carts can move as fleets, cutting control computation and coordination cost.

Dual-screen robot control separates live surroundings from selectable target icons, making remote navigation and interaction faster.

Separating transmit and return polarizations helps LiDAR detect weak object reflections with less interference in bright driving environments.

Independent collective and cyclic pitch with forward propulsion improves rotorcraft maneuverability, cruise efficiency, and emergency landing control.

Probabilistic safety regions let a household robot assess path risk in real time, avoid collisions, and keep moving efficiently.

A camera-axis-based control scheme links UAV motion to the pilot's view, simplifying rotary-wing inspection flight and reducing operator workload.

A route-based C2 link model flags in-flight deviations early, enabling prescribed UAV maneuvers before BVLOS connectivity is lost.

Variable-length suspension cables let multiple hover-capable aircraft orient and place a shared load precisely without changing aircraft altitude or attitude.

Three-dimensional image data lets a safety sensor determine its own position and switch protective fields without extra hardware interfaces.

By linking TCAS with the FMS, autopilot, and VNAV, this case cuts pilot workload and enables safe automatic evasive maneuvers.