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BeSAFEv2 Benchmarking Safety of Agents in Familiar Environments v2
Motivation: Create a realistic rendered benchmark to evaluate reinforcement agents, visual navigation tasks, interaction with other agents, navigation in scene with static and dynamic objects and humans.
How: Create a realistic rendered benchmark to evaluate reinforcement agents, visual navigation tasks, interaction with other agents, navigation in scene with static and dynamic objects and humans.
Not specified
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Requirements: experience with a Python deep learning framework, understanding of 3D scene and camera geometry.
Please send us a CV and transcript.
zbauer@ethz.ch blumh@ethz.ch boysun@ethz.ch
Requirements: experience with a Python deep learning framework, understanding of 3D scene and camera geometry.