Robot Vision & Automation Localization · D17

Bagged, Fabric and Deformable-Object Grasp Perception

JIVISION offers project development and technical assessment for Bagged, Fabric and Deformable-Object Grasp Perception. Scope: Flexible-object contours, keypoints, folds, graspable regions and deformation.

Scope and project-specific requirements

Task / output

Flexible-object contours, keypoints, folds, graspable regions and deformation

Critical decision conditions

Cloth and bags lack a fixed rigid pose; define graspable regions and gripping constraints by shape and material.

Candidate technical approach

These are candidate implementation paths. Establish a baseline on real samples, then select or combine methods for imaging, speed and deployment constraints. Model names do not imply measured project results.

Region segmentation and quantification

U-Net, DeepLabV3+, SegFormer or Mask2Former → connected components and morphology → region measurements

Keypoints and pose geometry

RTMPose, HRNet or MediaPipe keypoints → temporal filtering → joint angles, poses and spatial relationships

Optical flow and point trajectories

Shi-Tomasi/FAST features → LK, Farneback or DIS flow; alternatively TAPIR/TAPNext/RAFT → occlusion and drift handling

Stereo depth estimation

Stereo calibration and rectification → BM, SGBM or RAFT-Stereo → consistency checks and hole handling

Inputs for assessment

Provide robot/controller models, grippers/tools, parts or CAD, coordinate frames, working volume, camera mounts, control periods and interlock interfaces.

Deliverables and interface agreement

Result schema, algorithm or processing configuration, example outputs and evaluation records for: Flexible-object contours, keypoints, folds, graspable regions and deformation. Software format and source-code scope are agreed in the contract.

Specify input formats, output fields, coordinates/units, error states, versions and invocation methods. Define review and failure handling. The statement of work determines the exact scope of source code, executables, model files or analysis reports.

Acceptance method and measures

Task-specific acceptance measures

Keypoint error; grasp success; deformation-stratified results

Test visual localization error, calibration error, grasp/alignment success and end-to-end cycle time separately, including occlusion, empty scenes, changeovers and communication loss.

These are measures to agree and test, not achieved-performance claims. Freeze samples, reference truth, thresholds and hardware/software versions before acceptance; report subgroup results and failures, identifying under-sampled conditions as uncovered.

Implementation and procurement stages

  1. Define scope

    Agree targets, stations, inputs and responsibilities in a statement of work, separating required and excluded conditions.

  2. Sample validation

    Use representative samples to test critical risks, document feasibility/failures and scope the next-stage estimate.

  3. Development and integration

    Implement agreed functions and interfaces with configuration/change records; use offline replay before authorized device or site integration.

  4. Acceptance and handover

    Retest against individual measures and hand over contracted artifacts with known limits; manage maintenance, expansion and changeovers as subsequent work packages.

Scope limits and licensing

Vision output does not replace independent safety control. Responsible teams must verify robot motion, tooling and line interlocks before integrated testing.

Candidate technologies are not license clearance. Check code, model weights, training data and dependency versions separately. Replace, license or exclude components unsuitable for the intended commercial delivery. Customer data is not used for public training by default.

Project FAQs

What does this service produce?

Flexible-object contours, keypoints, folds, graspable regions and deformation. Deliverables: Result schema, algorithm or processing configuration, example outputs and evaluation records for: Flexible-object contours, keypoints, folds, graspable regions and deformation. Software format and source-code scope are agreed in the contract.

What needs to be confirmed first?

Cloth and bags lack a fixed rigid pose; define graspable regions and gripping constraints by shape and material.

How is acceptance defined beyond a demonstration?

Task-specific measures: Keypoint error; grasp success; deformation-stratified results. Test visual localization error, calibration error, grasp/alignment success and end-to-end cycle time separately, including occlusion, empty scenes, changeovers and communication loss.

How are cost and schedule assessed?

After reviewing samples for flexible-object contours, keypoints, folds, graspable regions and deformation, equipment conditions and interfaces, scope validation, development, deployment and acceptance separately. Data coverage, site changes and delivery rights affect the estimate; no fixed performance or schedule is promised before assessment.

PROJECT INQUIRY

Discuss this service for your project

Service ID: D17 · Bagged, Fabric and Deformable-Object Grasp Perception

Describe available samples, equipment and target measures. Agree confidentiality and permissions before transferring sensitive or personal data through an approved channel.

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