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Amap Tech

Jun 22, 2026 · Artificial Intelligence

Three Amap Papers Accepted at IROS 2026: VLN Navigation, VLA Latency Correction, and Diffusion‑Based Quadruped Control

IROS 2026 received 4,348 submissions and accepted 1,585 papers (36% acceptance); Amap had three papers selected, covering online semantic‑affordance navigation, an asynchronous edge adapter for VLA‑based navigation, and a diffusion‑guided constraint‑aware framework for high‑fidelity quadruped locomotion.

asynchronous VLA navigationdiffusion modelsembodied AI

0 likes · 8 min read

Three Amap Papers Accepted at IROS 2026: VLN Navigation, VLA Latency Correction, and Diffusion‑Based Quadruped Control

Amap Tech

Jun 18, 2026 · Artificial Intelligence

MapSatisfyBench: From Task Completion to Decision Satisfaction for Map Agents

MapSatisfyBench, a new benchmark co‑developed by Amap and Peking University, shifts map‑agent evaluation from simple task‑completion to quantifiable decision‑satisfaction by extracting implicit user demands via a restore‑identify‑filter pipeline, constructing a five‑dimensional truth schema and revealing that current LLM agents often complete tasks yet fail to meet hidden user preferences.

Decision SatisfactionFive-Dimensional MetricsImplicit Demand

0 likes · 14 min read

MapSatisfyBench: From Task Completion to Decision Satisfaction for Map Agents

Amap Tech

Apr 19, 2026 · Artificial Intelligence

From Pixels to the Physical World: Inside Gaode’s ABot Full‑Stack

Gaode leverages 20 years of spatiotemporal data to unveil a three‑layer ABot stack—World Model, navigation (N series), manipulation (M series) and a Harness architecture—that embeds physical laws, self‑evolves through a dual data‑training engine, and achieves benchmark‑leading performance across wheeled, quadruped and humanoid robots.

Navigationbenchmarkembodied AI

0 likes · 16 min read

From Pixels to the Physical World: Inside Gaode’s ABot Full‑Stack

Amap Tech

Apr 1, 2026 · Artificial Intelligence

Can World Models Truly Understand Interaction? Inside the Omni-WorldBench

Omni-WorldBench introduces a comprehensive benchmark that shifts world‑model evaluation from visual fidelity to interactive response, detailing its two‑part suite, metric design, extensive prompt taxonomy, and experimental results that reveal current models' strengths and limitations in causal and temporal reasoning.

AIOmni-WorldBenchbenchmark

0 likes · 11 min read

Can World Models Truly Understand Interaction? Inside the Omni-WorldBench

Amap Tech

Mar 30, 2026 · Artificial Intelligence

ABot-M0: A Unified VLA Framework Solving the One‑Brain Many‑Forms Robotics Challenge

ABot-M0 is an open‑source Vision‑Language‑Action foundation model that unifies fragmented robot data, introduces Action Manifold Learning for smoother action prediction, and offers a plug‑and‑play dual‑stream perception architecture, achieving state‑of‑the‑art results on major manipulation benchmarks.

action manifold learningembodied AIfoundation model

0 likes · 4 min read

ABot-M0: A Unified VLA Framework Solving the One‑Brain Many‑Forms Robotics Challenge

Amap Tech

Mar 20, 2026 · Artificial Intelligence

How ABot-PhysWorld Achieves Physical Consistency in Embodied Video Generation

ABot-PhysWorld introduces a physically consistent video generation framework for embodied AI, leveraging the PAI‑Bench benchmark, large‑scale multi‑modal data, DPO preference alignment, and dense action maps to surpass SOTA models in both visual quality and physical plausibility across diverse robotic tasks.

Deep LearningPhysical Consistencybenchmark

0 likes · 15 min read

How ABot-PhysWorld Achieves Physical Consistency in Embodied Video Generation

Amap Tech

Mar 5, 2026 · Artificial Intelligence

How MobilityBench Measures the Real Power of AI Route‑Planning Agents

MobilityBench is an open‑source benchmark built from over 100 000 real user queries that evaluates AI route‑planning agents with a deterministic sandbox, multi‑dimensional metrics, and support for ReAct and Plan‑and‑Execute frameworks, revealing performance gaps between open‑source and closed‑source models.

AI AgentsEvaluationMobilityBench

0 likes · 6 min read

How MobilityBench Measures the Real Power of AI Route‑Planning Agents

Amap Tech

Feb 13, 2026 · Artificial Intelligence

How ABot‑M0 Achieves Generalist Robot Intelligence with Action Manifold Learning

ABot‑M0 tackles the three long‑standing "Babel Tower" challenges of embodied AI—data fragmentation, inconsistent representations, and training mismatches—by releasing the massive UniACT dataset, introducing Action Manifold Learning for direct action prediction, and designing a plug‑and‑play dual‑path perception architecture that outperforms prior models on multiple robot benchmarks.

action manifold learningdatasetembodied AI

0 likes · 14 min read

How ABot‑M0 Achieves Generalist Robot Intelligence with Action Manifold Learning

Amap Tech

Feb 11, 2026 · Artificial Intelligence

Can Diffusion Models Turn Noisy GPS into Sub‑Meter Visual Localization?

The DiffVL framework redefines visual localization as a diffusion‑based GPS denoising task, using BEV‑conditioned visual cues and standard SD maps to achieve sub‑meter accuracy without high‑definition maps, and demonstrates its superiority through extensive autonomous‑driving experiments.

Autonomous DrivingBEVGPS denoising

0 likes · 11 min read

Can Diffusion Models Turn Noisy GPS into Sub‑Meter Visual Localization?

Amap Tech

Feb 5, 2026 · Artificial Intelligence

How UniMapGen Revolutionizes Large‑Scale Lane‑Level Map Generation with Generative AI

UniMapGen introduces a generative, multimodal framework that models lane lines as token sequences, employs an iterative state‑update mechanism for global consistency, and achieves state‑of‑the‑art performance on large‑scale satellite‑derived map construction, enabling seamless lane‑level navigation worldwide.

Autonomous Drivinggenerative AIlarge-scale mapping

0 likes · 10 min read

How UniMapGen Revolutionizes Large‑Scale Lane‑Level Map Generation with Generative AI