Deformable Cable Handling

Hook Latching

Challenge: Floating cables and compliant connectors introduce uncertainty during alignment and mating. Linear insertion attempts often fail due to misalignment and surface ambiguity.

Capability: CarbonSix leverages a contact-aware AI skill to detect insertion cues through physical interaction. It maintains controlled contact, adaptively retries when needed, and executes time-optimized motion to reduce takt time while preserving reliability.

HybridSkill

Challenge: Oscillating reflective hooks and positional variance in engine blocks disrupt stable insertion workflows. Pure rule-based control struggles with variability, while AI-only control may not fully optimize cycle time.

Capability: CarbonSix combines AI-based skills for adaptive perception and alignment with rule-based skills for deterministic high-speed execution. This hybrid skill architecture enables reliable and takt-time-efficient hook latching under dynamic conditions.

Precision Peeling

Coordinated Bimanual Manipulation

Challenge: Extracting a deformable timing belt from a transparent pouch requires precise dual-arm coordination. The pouch collapses easily while the belt twists unpredictably, making stable separation difficult for single-arm or fixed automation systems.

Capability: CarbonSix enables coordinated bimanual manipulation through intelligence-driven synchronization. One arm stabilizes the packaging while the other isolates and transfers the flexible component. The system maintains controlled interaction dynamics throughout separation and placement, ensuring stable downstream processing.

Arrangement

Assembly

Challenge: Dumplings appear in irregular orientations and positions, making it difficult for traditional systems to align them consistently. Fixed automation fails when dumplings vary in shape or layout.

Capability: Our technology perceives dumplings in unstructured states and intelligently re-orients them. It adapts flexibly to irregular arrangements, enabling accurate alignment before further processing.

Peeling-off

Cable Insertion & Fastening

Challenge: Thin, transparent, and fragile films are difficult to detect with traditional vision sensors. Irregular patterns and positional changes make stable handling nearly impossible, while the rigid motions of conventional robots often cause damage.

Capability: Our technology delicately detaches films without tearing, even under irregular conditions. By mimicking human-like fine force control, it achieves precision handling that minimizes damage and goes beyond traditional robotic performance.

Hanging

Challenge: Flexible materials such as bag straps or ton bags shift and sag unpredictably, making them difficult to handle.

Capability: Our technology accurately recognizes these variations and securely grasps deformable objects, enabling consistent and reliable hanging operations.

Hooking

Removal

Challenge: Hanging thin, reflective, and moving objects with accuracy is extremely difficult for conventional robots. Motion and glare disrupt stable detection, while the slender form makes secure grasping a challenge.

Capability: Our technology reliably detects and grasps even thin, reflective, and moving objects, placing them precisely where needed. It adapts with human-like finesse to complex and irregular environments.

Supported Robots