Programme-Controlled Manipulator TRIZ Cases

A mobile robot recalculates camera position and orientation from visual feedback to keep reference points in view and avoid manual re-teaching.

Two torsion spring-like spiral feet replace conventional wheels to maintain stable forward motion across rugged, irregular terrain.

Machine-learned motor intent prediction personalizes mobility actuation by comparing intended and actual movement and adjusting assistance in real time.

A pull-pull wire mechanism gives a compact robotic gripper strong, precise needle rotation and stable suturing in constrained endoscopic channels.

Spatial and timing feedback helps a control node track trajectory deviation and boundary limits despite wireless delay, jitter, and packet loss.

Predicted bandwidth and attention-based region selection tune video codec settings to preserve analytics accuracy in remote vehicle control.

Optical deviation detection lets one robot hand place multiple substrates separately with high accuracy while avoiding crack-causing contact.

Attention-guided compression and RL-tuned encoding preserve vision-model accuracy for teleoperated vehicles under changing bandwidth.

A roller lifting edge lets the contact section slide under flat or layered sacks, enabling precise gripping and transfer without protruding edges.

Machine learning predicts robot positioning error from reference coordinates, enabling faster compensation updates with less manual calculation.

A pseudo-sinusoidal passive torque mechanism supports forward-leaning work and straightening up while reducing strain without added actuator weight.

A removable gripper unit shares one imaging base, cutting sensor cost while adapting image analysis to different object shapes.

A social robot infers user mood from interaction cues to select media or control connected devices for more responsive assistance.

Video-based robot teaching captures operator actions and sensor data to cut reprogramming time while keeping object handling precise and flexible.

A unified world-coordinate model couples chassis and arm motion, reducing repeated pose adjustments while improving precision and fluency.

Forward kinematics and trajectory interpolation let a robot quickly correct limb-to-instrument position changes without extra sensors.

A unified robot interface adds cloud image handling, calibration, and live setting control to make robotic artwork creation easier across different drawing robots.

A cart recess nests part of the robot to stabilize robot-cart positioning, simplifying dual-arm gripping and transport control.

RF tracking and Cartesian axis control improve surgical instrument positioning accuracy while reducing manual alignment effort.

Image slicing and text-image embeddings generate dense rewards for robotic policy learning without handcrafted shaping or historical task data.

Audio, movement, and user-profile analysis enable conversational AI to tailor responses, voice, and gestures for more engaging interaction.

Interchangeable tracking arrays give one surgical robot procedure-specific fields of view while preserving tracking accuracy and sterility.

Optical emitters and receivers detect end-effector deflection and pitch abnormality early to prevent substrate damage during transfer.

Graph-based tokenization and GNN encoding preserve relationships in robotic perception data, improving decision-making in complex environments.

Automatic coordination of robotic instruments and camera movement preserves remote centers of motion, cutting tool transition time and risk.

Balances robot automation cost, productivity, and performance by evaluating work procedures and suggesting configuration changes.

Sensors and an alignment drive correct docking gaps and misalignment, enabling reliable sample carrier transfer in laboratory automation.

Dual-camera feedback corrects print drift on moving workpieces, maintaining placement accuracy without shutdowns or manual recalibration.

A nested three-axis transmission structure lets an in-vehicle robot simulate realistic human head motion without relying on only two-direction rotation.

Adjustable modular robot arms map protective gas velocity, temperature, and oxygen across AM chambers to improve fume and spatter removal.

Unified trajectory planning, inverse kinematics, and decoupling synchronize chassis and arm motion to raise mobile robot efficiency on production lines.

Vacuum end effectors and indexing assemblies preserve contoured composite curvature during transfer onto a moving mandrel, cutting line time and cost.

Captured screenshots are clustered to identify repeated UI actions across platforms, enabling automated RPA workflow generation with less manual analysis.

Sensor-based teat spacing detection lets the robot choose the first teat for cup attachment, preventing jamming and improving milking throughput.

Dual gantries and gripping units automate wide fiber ply pickup and placement in blade molds, improving layup accuracy, speed, and safety.

Force and position feedback let the feeder detect engagement state, prevent shaft slack, and avoid improper loading during robotic procedures.

Electronic RCM control replaces bulky mechanical linkages in a surgical robot arm, reducing size, improving space efficiency, and preventing collisions.

Torque-based door presence detection lets a robot open and close vehicle doors accurately while avoiding interference in coating lines.

A multi-stage vision and reasoning pipeline helps indoor surveillance robots detect hazards, read signages, infer violations, and trigger alerts.

Depth and visual difference masks turn before-and-after stack images into segmentation labels, cutting manual annotation for robotic picking.

Image capture and distance sensing calculate article face positions before pickup, enabling faster cargo handling with steadier grasping and less damage.

Lidar map matching scores and confidence evaluation refine an initial robot pose, improving relocation accuracy without unnecessary computation.

A wheel suspension with swing rods, springs, and damping plates reduces vibration and tip-over risk in autonomous warehouse picking robots.

A learned model predicts future states from state data and plan sequences to score long-term robot control feasibility before execution.

An integrated transmission and composite drive joint delivers 3-DOF robot motion with lower weight, less complexity, and higher control accuracy.

An oil-filled glove equalizes deepwater pressure so a robotic hand can measure clamping force reliably and grasp fragile objects.

Flexures in a parallelogram RCM joint relieve overconstraint, enabling predictable exoskeleton rotation with lower tolerance sensitivity.

3D point cloud bracket sensing helps photovoltaic robots correct pose in real time, improving installation accuracy and detecting abnormal alignment.