pith:NPZFDOKU
ShapeGrasp: Simultaneous Visuo-Haptic Shape Completion and Grasping for Improved Robot Manipulation
ShapeGrasp updates object shape models with tactile data from real grasps to improve subsequent planning and success rates.
arxiv:2605.02347 v2 · 2026-05-04 · cs.RO
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\pithnumber{NPZFDOKUAWDFM6VYYLDSD63WP3}
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Record completeness
Claims
To the best of our knowledge, this is the first approach that updates shape representations following a real-world grasp. We achieved superior results over baselines for both grippers (grasp success rate of 84% with a three-finger gripper and 91% with a two-finger gripper), while improving the 3D shape reconstruction quality in all evaluation metrics used.
That the fusion of tactile surface contacts and gripper body occupancy with the initial visual estimate produces a sufficiently accurate updated shape model to enable reliable subsequent grasp planning in real-world conditions.
ShapeGrasp improves grasp success on unknown objects to 84-91% by iteratively updating a 3D shape model with visuo-haptic feedback during real-world grasp attempts.
Formal links
Receipt and verification
| First computed | 2026-07-01T01:17:51.466015Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6bf251b9540586567ab8c2c721fb767ef1170c244a9a14133950fdce92465626
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NPZFDOKUAWDFM6VYYLDSD63WP3 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 6bf251b9540586567ab8c2c721fb767ef1170c244a9a14133950fdce92465626
Canonical record JSON
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"submitted_at": "2026-05-04T08:49:52Z",
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