Programme-Controlled Manipulator TRIZ Cases

Weight-based checking lets a robot detect double picks during singulation, avoiding AI training overhead while improving handling of mixed objects.

An edge interface captures IMM and robot control signals to detect instability, trace defects, and enable real-time molding adjustments.

Modern computer vision and reinforcement learning replace costly picking hardware, enabling autonomous fruit harvest with grading and storage.

Tactile sensor feedback reshapes manipulator impedance during contact to cut collision energy transfer without sacrificing tracking accuracy.

Trajectory data separates crusher grasping and sorting motions, cutting manual video analysis time while preserving detailed operator assessment.

Physical replica workpieces and tools let operators detect machining collisions safely during setup without risking damage to original components.

Internal air and vacuum passages compact the suction gripper, cut protrusions, and simplify cleaning and maintenance in handling lines.

Separating 3-axis linear positioning from 3-axis rotary posture control enables compact, high-speed, accurate dual-end-effector work.

Labeled MDPs map each robot skill to control conditions, enabling mixed robot teams to execute shared missions under one framework.

Camera-guided welding and grinding repair platen surface defects inside a hot press, cutting multi-day shutdowns and confined-space manual work.

Three robots with different axis layouts work on moving workpieces from multiple sides, raising throughput without workspace interference.

Image-based product analysis determines routing, trajectory, and end effector choice to reduce warehouse misplacement and handling damage.

Shared monitoring lets nearby robots cover sensor blind spots, improving factory robot safety without adding more onboard sensors.

A single camera and mirror capture both workpieces at once, enabling feedback control for more precise relative alignment during assembly.

Simulation and real-world feedback are combined to tune industrial application parameters faster while reducing hardware risk and reality-gap errors.

Machine learning and coating simulation generate collision-free robot coating programs that meet target thickness ranges with less programming effort.

Switching between filtered and original torque signals suppresses robot resonance while preserving accurate position and force control.

Projects robot status and action cues directly into the monitored workspace, avoiding noisy audio alerts and attention-shifting warning lamps.

Predicted scan data lets a robot assess collision risk and generate driving commands with less computation than full object tracking.

A fixed camera-projector pair lets a cobot project warnings and gesture-based guidance into the shared work area, avoiding noisy audio cues.

An autonomous mobility cart retrieves store orders and delivers them to a shopper's vehicle with live status updates and delivery confirmation.

Independent robotic legs and arms let this service vehicle walk, drive, stabilize on uneven ground, and handle objects in real time.

A camera-guided robot tracks wood on a cross conveyor to identify and remove defective pieces at high speed while maintaining sorting quality.

Independent comparison and mutual monitoring sections detect encoder or safety-control failure and cut robot arm drive power before unsafe motion.

A planetary speed reducer layout cuts heat and inertia, enabling faster conveyance arm acceleration in limited space.

A ground robot carrying and wirelessly charging a micro drone expands patrol reach into inaccessible terrain while extending surveillance time.

Radar sensors mounted on a robotic arm create a conformal safety envelope that detects people and obstacles without physical barriers.

Machine learning links robot configuration and process parameters to detect anomalies, cut false alarms, and reduce storage needs.

Automatically generates a surface-aligned projection view so operators can mark robot work regions quickly and convert them back into 3D space.

Force/torque feedback and mirror descent guided policy search help robots learn precise contact-rich assembly without lengthy trial-and-error.

Manual robot guidance is converted into a smoothed motion program by recording TCP points and removing extraneous movements.

Geometric algebra and CSG speed robot grasp point estimation by simplifying oriented distance calculations across varied object shapes.

Sensor data and biomechanical modeling predict instability, then selectively stiffen actuators to block fall-prone motion.

Joint torque is used to calculate ground reaction forces and estimate robot center of gravity without fragile force sensors.

Logical task expressions are converted into atomic potential functions, letting non-experts build robot control objectives for complex tasks.

Nonlinear optimization generates feasible mobile manipulator trajectories that satisfy joint limits, avoid collisions, and improve warehouse task agility.

Sequential actuator-driven end deformation releases a cut composite tube from a tapered mandrel without disassembly, damage, or splice joints.

Combined 3D point cloud data and machine learning let a robotic handler choose picking or sweeping modes for faster vehicle loading and unloading.

Selective suction zones and vision-based overlap checks let robots pick mixed boxes in walled containers without wall collisions or box slipping.

Precomputed identification trajectories let robotic manipulators estimate changing payloads quickly and improve control precision in real time.

A repositionable robotic welding arm uses yaw, pitch, and roll control with force limits to weld long pipe spools precisely and safely.

Console-free robot arm control tracks a second instrument or direct arm contact to improve laparoscopic precision while saving operating-room space.

Deformation ratios from multiple suction cup regions are checked without holding a workpiece, enabling easy wear detection and timely maintenance.

Adaptive HSV image recognition extracts product location and shape under lighting noise, enabling robot self-teaching for grasp and transfer.

Recent in-view calibration images let robot control refresh camera parameters and flag deviations before outdated calibration causes motion errors.

Adaptive RGBW LEDs built into gripper fingers reduce occlusions, shadows, and blur while improving visual detection of fragile sub-centimeter objects.

Automated teaching and tool management cut operator programming effort in collaborative work cells while improving execution speed and safety.

Robots share trajectory data over a network to detect collision risk and automatically correct motion without robot-specific region programs.

Optical imaging checks drill-bit color and wear marks in wall drilling, enabling early replacement before overheating or failure.

A controller detects whether a partner machine is real or virtual, then adapts processing to support mixed real-virtual system simulation.