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Robots excel in performing repetitive and precision-sensitive tasks incontrolled environments such as warehouses and factories, but have not been yetextended to embodied AI agents providing assistance in household tasks.Inspired by the catalyzing effect that benchmarks have played in the AI fieldssuch as computer vision and natural language processing, the community islooking for new benchmarks for embodied AI. Prior work in embodied AI benchmarkdefines tasks using a different formalism, often specific to one environment,simulator or domain, making it hard to develop general and comparablesolutions. In this work, we bring a subset of BEHAVIOR activities into Habitat2.0 to benefit from its fast simulation speed, as a first step towardsdemonstrating the ease of adapting activities defined in the logic space intodifferent simulators.

BEHAVIOR in Habitat 2.0: Simulator-Independent Logical Task Description for Benchmarking Embodied AI Agents