Vehicle Position/Course/Altitude Control TRIZ Cases

A dual embedded control split speeds obstacle detection and motor response, improving reliable real-time avoidance for fast industrial robots.

Preliminary obstacle checks on an oncoming lane help unmanned vehicles avoid delays and collisions while staying on designated site paths.

Hierarchical tactile feedback lets a snake robot switch and tune gaits in real time, improving traversal on uneven, obstacle-filled terrain.

A movable virtual viewpoint and reach-based operable range make 3D mobile object control more intuitive without prior spatial maps.

Sensor-event mapping recommends behavior control zones so autonomous robots avoid obstacle-prone areas and reduce stuck events during cleaning.

A touch interface and directional lidar let the UAV hold constant distance and view alignment for simpler semi-autonomous inspection in complex spaces.

Capability prediction and control allocation decouple tiltable rotorcraft position and attitude while preventing instability beyond control limits.

Historical maritime traffic maps and INS uncertainty guide UUV surfacing points to limit collision risk, path length, and GPS resets.

Point cloud obstacle typing and multi-sensor validation improve autonomous mobile obstacle avoidance when Lidar errors reduce detection precision.

Sensor-based angular offset control shifts reverse propulsion to the trailer wheels for precise docking in confined spaces with less steering.

Image sensors let a pool cleaner leave a sparse main path for detected debris, then return, improving coverage while cutting power use.

Point-cloud tunnel detection lets a mobile machine adjust safety margins to pass narrow spaces while maintaining collision avoidance.

Handheld attitude sensing and a head-mounted direction marker make UAV control more intuitive while helping users anticipate flight path and collisions.

Radar-based relative positioning corrects a robot's distance and angle to object edges, preventing falls on soft cotton or silk surfaces.

Context-based LIDAR and radar power switching extends range where needed while cutting vehicle sensor energy use.

Forward traffic simulation predicts road-user positions ahead of transmission delay, improving remote driving awareness and control stability.

Vision-based UAV control adapts 3D flight paths to changing object contours, enabling obstacle avoidance and tracking with less manual input.

Somatosensory remote motion and inertial sensing let a UAV hold selfie distance and position more intuitively, improving image capture quality.

Threat path sensing and closest-approach calculation let a stationary drone descend to a safe altitude when air or ground hazards approach.

A modular frame, configurable controller, and LiDAR/TOF sensing let one autonomous cart handle varied payloads and navigate tight spaces.

Using certified FMS functions, this case maintains fixed aircraft separation on non-coincident flight paths without a separate interval computer.

Passive landmarks and dual laser rangefinders replace GNSS or powered beacons to give worksite platforms accurate positioning and orientation.

Sensor fusion and floor-plan generation help a mobile robot avoid obstacles, map room coverage, and trigger complementary tasks on a second device.

Layered aerial vehicle operation zones separate speeds and altitudes to cut collision risk and improve urban traffic flow.

Real-time bounded-variable optimization selects actuator mixes from sensor and health data to cut control error and power use.

Nonlinear power and energy prediction helps aerial vehicles reroute or shorten flight paths before reserves fall short.

Coaxial forward rotors balance yaw and roll moments after lifting-rotor loss, cutting overload on remaining motors and improving control.

Dynamic route overlays and teaching-based visual cues help remote operators guide working vehicles with less control difficulty.

Non-linear power and energy models help aerial vehicles predict flight path consumption and trigger contingency actions before reserves run short.

Adaptive attitude control with parameter estimation and dwell-time switching keeps foldable quadrotors stable through in-flight configuration changes.

Distance-sensor inputs and prior movement data feed a neural network so a robot can navigate unknown spaces faster without a pre-created map.

Current flight parameters are synced to a mirror FMS so offboard validation matches real aircraft conditions and catches corrupted incoming data.

Robust invariant sets are inflated around vehicle setpoints to keep trajectories safe under disturbances while reducing motion planning burden.

Magnetic connectors let monocopters join for cooperative flight and separate by centrifugal force, avoiding dedicated actuators.

Three physically separate processing pathways validate navigation and commands by majority voting to deliver high-integrity drone avionics with lower weight and cost.

Dividing a mowing area into convex sub-areas and aligning paths to each main extension direction cuts turning in narrow zones and improves coverage efficiency.

Graphical map inputs are translated into asset-specific journey plans, reducing commander workload in manned-unmanned operations.

A server sets a robot stop pose outside a restricted region so workers can reach task locations without obstruction or extra path adjustments.

A lightweight 3D range-sensor pipeline detects cliffs, ramps, and holes while reducing memory and processor load for safer robot navigation.

Position data collected as the lawnmower leaves its dock is line-fitted to calibrate charging station orientation accurately without dual RTK antennas.

Barometric altitude cross-checking between lead and follower aircraft flags unsafe formation geometry beyond vortex height margins.

A LIDAR-RADAR workflow checks line of sight and interference before monitoring target regions, improving moving-object detection under occlusion.

Compares lead and trailing aircraft barometric altitude to detect unsafe formation spacing and trigger cockpit collision warnings.

A 3D virtual platform model lets users confirm target points along a simulated trajectory, improving path safety, connectivity, and accuracy.

A counter-moving trigger layout packs flight and vehicle controls into one handheld unit, reducing bulk while preserving portable operation.

Map-based virtual boundaries replace physical markers, cutting setup time and cost while controlling autonomous working vehicle actuators.

Past correction shift data is reused to limit repeated position and azimuth corrections, keeping automatic work vehicle travel stable in rough fields.

LiDAR point clustering and feature extraction help autonomous vehicles identify suspended loads and halt before collision risk.

Neural-network control replans drone paths and sensor orientation as target areas change, cutting observation time and overlap.

RF reflections and point-cloud correlation let cooperative drones distinguish and locate an uncooperative vehicle within a swarm.

Multivariate track and refill planning cuts autonomous vehicle travel distance, coverage time, and replenishment interruptions.

When route direction diverges from the destination line, instant turning and route regeneration help mobile objects avoid inefficient paths.

3D weather blocks built from 2D weather data help autonomous aircraft assess risk in real time and reroute around hazardous conditions.

By mapping tempo constancy and key to pseudo-emotion, the robot moves beyond rhythm-only actuation to deliver more lifelike interaction.

A flight controller maps no-fly zone boundaries as virtual walls and changes UAV deceleration rates to prevent restricted-area entry.

Asynchronous LiDAR and IMU data are time-aligned to generate accurate HD maps and odometry for autonomous vehicle localization.

Real-time position and velocity transmission lets a UAV intercept a falling object accurately even when wind or no propulsion causes path fluctuations.

Multi-sensor target detection guides AUV ascent from safety depth to periscope depth, avoiding surface collisions without external control.

Force-sensing seats and IMUs estimate seated torso lean and twist to deliver hands-free control of robotic devices or avatars.

Camera geometry and motor-angle calibration let a pet robot place a laser spot precisely from touchscreen input or autonomous tracking.

Rotating prism and mirror optics widen LiDAR scanning coverage while preserving beam resolution without moving the full sensor unit.

Probability maps from drone positions and area data narrow likely operator locations, helping security teams respond to unauthorized flights.

Multiple UAVs keep fixed relative positions to cargo to stabilize heavy or long aerial transport and avoid posture misalignment.

Dual horizontal and vertical light scans compare reflection patterns to reject false obstacle alarms from highly reflective walls and floors.

Automatic signal detection switches a vehicle from remote-control standby to active mode, removing manual activation steps and improving operation.

Coordinated standard AGVs form a reconfigurable carrier that cuts vibration, improves stability, and adapts to large object transport.

Shared teleoperations guidance helps autonomous vehicles bypass obstacles by sending a point-of-intent and selecting a viable path without full remote driving.

Safety-scored queueing and operator matching cut response delay when multiple autonomous vehicles need remote guidance at once.

Mixed movable-rack and case conveyance uses vertical storage and size-based handling to cut travel distance and improve warehouse throughput.

Angled ultrasonic sensors with overlapping coverage let a self-moving mower steer around obstacles without stopping, preserving cutting continuity.

Light patterns built into a mobile robot joystick show autonomous or manual mode, improving status visibility for operators and nearby people.

Virtual driving lines and passage-time priority cut multi-robot route complexity while preventing collisions and deadlocks.

A GPT-driven robotics OS generates configuration and service files quickly while watchdog validation helps prevent unsafe failures and attacks.

Real-time carton scoring and AGV cart assignment balance picking workloads across fulfillment areas while improving throughput and cycle time.

When a work zone blocks autonomous driving, the vehicle seeks a reroute or hands off to teleoperators to maintain safe operation.

Keeping the home point fixed on the terminal display helps UAV operators maintain orientation as the aircraft moves and changes direction.

By computing near and far obstacle boundaries, the mobile apparatus selects a safe clearance path and avoids collisions with moving or priority objects.

UWB tag and anchor mapping records obstacle positions so a concrete pump boom can plan collision-free movement in tight construction sites.

A two-stage route plan guides mobile robots into elevators by separating approach and boarding paths to avoid wall collisions.

Preselected refuge stops and a higher override threshold help automated vehicles avoid traffic disruption and collision risk at intersections.

Pre-assigned shipment priority guides vehicles through converging routes, cutting delays and simplifying passage control during production-to-shipment transport.

Smaller robots split path planning and lifting to move heavy vehicles in tight parking spaces with lower energy use and better space utilization.

Stored shift amounts from earlier corrections help a work vehicle limit repeated position and azimuth adjustments on uneven or inclined fields.

Adaptive LIDAR scanning boosts angular resolution only around reflective features, improving edge, motion, and distant object detection.

Real-time landing cues, obstacle alerts, and automatic trajectory correction improve safe vehicle touchdown in constrained urban zones.

Autonomous fab layout learning lets a mobile stocker relocate quickly and reconnect to transport systems with less downtime.

Sequencing robot deliveries by outbound order keeps same-order materials flowing to one workstation without mixing or sorting errors.

A sealed transparent-substrate transmitter integrates emitters, collimation, and waveguides to protect lidar optics from moisture while staying compact.

A multi-camera panoramic UAV view lets operators observe targets from any angle without repositioning the aircraft, with stabilized video.

Flight path planning lets a fixed-camera UAV hold a target pitch angle longer for sharper still images without gimbal weight or complexity.

Dynamic boarding order and edge-based control cut latency and improve autonomous storage unit transport across sites.

A trained demand model helps allocate service providers and equipment by region, avoiding peak understaffing and resource waste.

Time-of-flight sensing extracts map-matched features for accurate robot localization when low light makes camera-based line detection unreliable.

A robot-mounted GPR follows planned survey paths to collect precise subsurface data in hazardous or inaccessible areas with less manual effort.

Sensor-based object valuation guides robot routes, posture, and handling to protect high-value items without slowing all movement.

Sensor-based supervisory robots detect soiling and dispatch service robots only where needed, improving floor cleaning quality with less manual spot work.

Automated gimbal speed and angle control lets a UAV capture camera-roll video accurately over long flight distances with less manual input.

Predicted leader positioning and follower trajectory planning improve tethered platform maneuverability while reducing unwanted tether forces.

Filtering sensor data below cow torso level removes leg interference, improving unmanned vehicle localization in free-cow areas.

Amplitude-modulated FMCW LiDAR separates range and Doppler information to speed target acquisition and reduce short-range aliasing.