Intelligent Automation for Embodied Benchmark Construction: Pipelines, Embodiments, Simulators, and Trends
arXiv:2606.12207v1 Announce Type: cross Abstract: Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control. This expansion has made benchmark construction a central bottleneck for reliable evaluation. Unlike static datasets, embodied benchmarks combine task specifications, environments, robot data, demonstrations, annotations, metrics, evaluation scripts, and release policies into a single evaluation system. This survey reviews the literature through a five-stage construction pipeline: requirement and
The rapid expansion of embodied intelligence across diverse applications has made benchmark construction a critical bottleneck, prompting a need for standardized and automated evaluation methods.
Reliable and scalable evaluation benchmarks are essential for the advancement and trustworthy deployment of embodied AI systems, impacting investment decisions and development priorities.
The focus is shifting towards intelligent automation of benchmark construction, moving beyond static datasets to comprehensive evaluation systems that include task specifications, environments, and robot data.
- · AI research institutions
- · Robotics companies
- · Embodied AI developers
- · Benchmark tool providers
- · Companies relying on ad-hoc evaluation
- · Developers with poor testing methodologies
- · Outdated benchmarking companies
More efficient and reliable development cycles for embodied AI systems will accelerate their market readiness.
Standardized benchmarks could lead to consolidation in the embodied AI market as performance can be more objectively compared.
The automation of benchmark creation might democratize access to advanced evaluation, allowing smaller players to compete effectively with larger labs.
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Read at arXiv cs.AI