Pith Number

pith:EEWQOPML

pith:2026:EEWQOPMLWAUB5MAYLPVRWBJEMC

not attested not anchored not stored refs pending

Optimizing Trajectory-Trees in Belief Space: An Application from Model Predictive Control to Task and Motion Planning

Camille Phiquepal, Marc Toussaint

Trajectory-trees optimized in belief space capture observation-dependent contingencies that sequential paths miss.

arxiv:2605.01860 v2 · 2026-05-03 · cs.RO

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\pithnumber{EEWQOPMLWAUB5MAYLPVRWBJEMC}

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4 Citations open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Trajectory-trees, optimized in belief space, naturally capture this dependency by branching where the belief state is expected to evolve into multiple distinct scenarios, such as upon receiving an observation. Unlike sequential trajectories, which model a single forward evolution of the system, trajectory-trees capture multiple possible contingencies.

C2weakest assumption

That the belief-state evolution and branching points can be accurately predicted and optimized in advance without prohibitive computational cost, particularly under the real-time constraints of MPC and for larger belief spaces in TAMP.

C3one line summary

Optimizing trajectory-trees in belief space improves performance in partially observable robotic planning by capturing observation-dependent contingencies, shown via PO-MPC with D-AuLa optimization and PO-LGP extending LGP.

Receipt and verification

First computed	2026-08-11T01:24:47.638818Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

212d073d8bb0281eb0185beb1b052460a57cca2fbd27a3f030092cd0f5cb8b1a

Aliases

arxiv: 2605.01860 · arxiv_version: 2605.01860v2 · doi: 10.48550/arxiv.2605.01860 · pith_short_12: EEWQOPMLWAUB · pith_short_16: EEWQOPMLWAUB5MAY · pith_short_8: EEWQOPML

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/EEWQOPMLWAUB5MAYLPVRWBJEMC \
  | 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: 212d073d8bb0281eb0185beb1b052460a57cca2fbd27a3f030092cd0f5cb8b1a

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4682da7e0c09c1d925153f7df9972c03767a9f26e16ccdff79cbc027566250c7",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-03T13:06:20Z",
    "title_canon_sha256": "73b30004fefd6dfeaa237031e74793a9a6950dbb23720720e97f8f2126602c25"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.01860",
    "kind": "arxiv",
    "version": 2
  }
}