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Coding Agents for Generalized Task and Motion Planning Problems

Paper recorded by Signals 4 on 2026-09-24 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-24 on arXiv · recorded by Signals 4 on 2026-09-25

Category: cs.AI · 人工智能 · first seen 2026-09-25

Abstract

Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discrete decisions are tightly coupled to geometric, kinematic, and dynamic constraints. Generalized TAMP addresses this difficulty by exploiting regularities across problem instances to reduce planning effort on new instances. However, existing methods require substantial TAMP-

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#5 most recent of 400 cs.AI papers we have recorded · ↑ newer: Rolling-WAM: World Action Models with Rolling Imagination · ↓ older: To Trust or Not to Trust: Retrieval-Augmented Fact Checking in Speech

Cite this page: Coding Agents for Generalized Task and Motion Planning Problems: the #5 most recent of 400 cs.AI papers we have recorded (as of 2026-09-24). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/coding-agents-for-generalized-task-and-motion-planning-problems.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json

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