perceiving-sorting-pairs
De la autor
Discovers a labelled four-compartment destination from RGB-D and repeatedly perceives one remaining source object with its matching metric destination region, using an identity table the graph supplies for what each label looks like and what its graspable part is called. Use when a workflow must sort several visible objects into compartments identified by printed category labels.
Instalare
npx skills add graph-robots/open-robot-skills --skill perceiving-sorting-pairs -a claude-code
Se instalează în .claude/skills/perceiving-sorting-pairs/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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De ce 76
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- perceiving-next-itemgraph-robots/open-robot-skillsLoop-head perception for pack-all / clean-all-items tasks. From ONE observation it localizes BOTH the destination container (basket, bin, box) AND the next remaining target item, using the pairwise VLM crop tournament with a container-excluding description so the target is never confused with the basket, then makes a clean found / none decision: an item was found (grasp it) or only the container remains (all items packed — exit the loop to done). Use when a workflow must pick up EVERY object and place each into a container in a loop (pack-all / clean-all-items) and each pass must reliably answer "is there still a graspable item, or are we done?" while also exposing a fresh container OBB for the downstream place. This subgraph is self-contained and takes NO inputs (inputs: {}); the container and item phrases are literal strings written inside the perception nodes, never subgraph parameters — do not declare item_name / container_name / item_description as subgraph inputs.Redactare★ 58
- perceiving-functional-featuresgraph-robots/open-robot-skillsLocates a language-described functional part of a rigid object or fixture from calibrated RGB-D and fits a typed loop, shaft, tip, aperture, surface, or region feature with a metric centre, axis, and radius, either inside an already-segmented parent or end to end from a described object, protruding shaft, directed tip, or lidded aperture. Use when a manipulation step depends on where a specific part is rather than on the whole object, such as a tool loop to hang, a shaft to hang it on, an insertion tip, or an opening to insert into.Planificare★ 58
- perceiving-routing-fixturesgraph-robots/open-robot-skillsSurvey a cable-routing bench from one overhead RGB-D frame — find every station (spool, cleat) by colour, roundness and height off the work surface, fit the cable's ordered centreline through a text-prompted segmenter, derive the side each crossing owes from the instruction's alternation, and place the physical seat beside each post. Use when a routing plan needs the fixture layout and the starting shape of a deformable linear object, once, before the first move.Planificare★ 58
- perceiving-object-partsgraph-robots/open-robot-skillsHierarchical perception for subpart targeting. Detects a parent object first (DINO+VLM), crops the camera image to the parent's bounding box, then detects and segments the named subpart inside the crop (DINO + SAM3), and uncrops + fuses depth to a world-frame OBB/mask/cloud — plus the parent object's OBB and cloud for downstream placement/collision reasoning. Use when the graspable affordance is a subpart of a larger object — pan handle, drawer pull, mug rim, moka-pot handle, stove burner — where detecting the subpart at full image resolution is unreliable because it occupies few pixels.Media★ 58
- product-pairAlpacaLabsLLC/skills-for-architectsSuggest complementary products that pair well with a given item — side tables for sofas, task lights for desks, etc. Use when the user asks "what goes with" a product, wants coordinating pieces, or asks to complete a furniture grouping.Productivitate★ 390
- perceiving-deformable-linear-objectsgraph-robots/open-robot-skillsRead a cable's ordered 3D centreline from one RGB-D frame and keep it current across a task — seed it from an unobstructed survey, re-fit it cold whenever the whole rod is in view, and fall back to tracking the carried prior only when the fresh fit comes back short. Use when a manipulation loop needs the current shape of a deformable linear object (a cable, rope, or hose) once per step rather than every frame, from a fixed third-person camera.Productivitate★ 58
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