# EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots

Page: https://stenobird.com/podcast/daily-paper-cast-7079649/eva-client-a-unified-data-collection-inference-and-deployment-framework-for-embodied-policies-on-real-robots
Text version: https://stenobird.com/podcast/daily-paper-cast-7079649/eva-client-a-unified-data-collection-inference-and-deployment-framework-for-embodied-policies-on-real-robots.md
Podcast: [Daily Paper Cast](https://stenobird.com/podcast/daily-paper-cast-7079649)
Published: 2026-07-08T03:18:58+00:00
Episode link: https://share.transistor.fm/s/ad2d40dc
Audio file: https://media.transistor.fm/ad2d40dc/de93ac07.mp3
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JSON: https://stenobird.com/v1/public/podcasts/daily-paper-cast-7079649/episodes/eva-client-a-unified-data-collection-inference-and-deployment-framework-for-embodied-policies-on-real-robots
Duration seconds: 1350

## Resource

🤗 Upvotes: 23 | cs.RO, cs.CV Authors: Heqing Yang, Yang Yi, Liyao Wang, Linqing Zhong, Donglin Yang, Ruipu Wu, Zitong Bai, Fengjiao Chen, Manyuan Zhang, Linjiang Huang, Si Liu Title: EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots Arxiv: http://arxiv.org/abs/2607.02646v1 Abstract: We present EVA-Client, an open-source framework for deployment, data collection, and evaluation of trained manipulation policies on real robots. Sitting between a policy server and the physical hardware, EVA-Client unifies the real-robot stages of the policy iteration loop within a single codebase. It makes three contributions. First, a component-decoupled architecture in which robot backends, inference strategies, and transport middlewares form an orthogonal grid: adding a robot or a strategy touches only its own layer. Second, inspectable execution through Debug, Collect, and Eval workflows, with modes ranging from open-loop simulation to continuous real-time control. Third, every evaluation run doubles as a data collection, recording full rollouts in training-ready format alongside exhaustive logs and a side-by-side comparison viewer, so each evaluation feeds the next round of training rather than ending as an unrecorded impression. EVA-Client further consolidates major real-time inference strategies, synchronous and asynchronous execution, ACT-style temporal ensembling, Real-Time Chunking, and a naive-async ablation baseline, behind a single configuration surface.

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