Spot social nav #1658
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Spot social nav #1658
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habitat-lab/habitat/tasks/rearrange/multi_task/pddl_sim_state.py
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* tyde CI * getting a corrcet init location of arm * tidy CI * sensor clean up so that the size is the same * setup social nav reward and yaml * bounding box update * clean up human bbox detector * tidy * tidy * add stereo pari camera * make the size of HumanoidDetectorSensor consistent with the senser obs * fix nan issue * fix init_distributed issue * tidy * tidy CI and add comments * add more comments * tidy CI * add InitialGpsCompassSensor sensor * refine social nav reward * add exploration reward * increase the video size * polsih the PR * tidy * reduce the third_rgb_sensor size --------- Co-authored-by: Jimmy Yang <[email protected]>
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* tyde CI * getting a corrcet init location of arm * tidy CI * sensor clean up so that the size is the same * setup social nav reward and yaml * bounding box update * clean up human bbox detector * tidy * tidy * add stereo pari camera * make the size of HumanoidDetectorSensor consistent with the senser obs * fix nan issue * fix init_distributed issue * tidy * tidy CI and add comments * add more comments * tidy CI * add InitialGpsCompassSensor sensor * refine social nav reward * add exploration reward * increase the video size * polsih the PR * tidy * reduce the third_rgb_sensor size --------- Co-authored-by: Jimmy Yang <[email protected]>
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Motivation and Context
This PR improves the design of the social nav. It is designed specifically for learning a social nav policy for the Boston Dynamics Spot robot. The major changes compared to the base yaml are the following:(1) obs_keys: we ensure these observations can be obtained from the real robot (Spot)
(2) social_nav_reward: social nav reward considers collisions based on a kinematic simulation
(3) actions: Spot controls the base linear and angualr velocity
(4) simulator: we simulate the environment via the kinematic mode to facilitate sim2real transfer
In addition, this PR provides a couple of improvement:
(1) Fix the bug calling
_agent.init_distributed()(2) Allow the social nav reward function takes the kinematic force termination info
(3) real world spot sensors
This PR is tight to the theme of Better Documentation/Better Engineering
How Has This Been Tested
Complete a full sweep of hyper-parameters (collision penalty), and the training reward improves in 4 days of learning.Types of changes
Checklist