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feat(evals): ABC Sim suites on OpenYAM - #5259
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go2 replay realtime (arm64)
Details
| Benchmark suite | Current: a782cde | Previous: 5e0ebfd | Ratio |
|---|---|---|---|
peak memory |
1739.906 MB |
1715.605 MB |
1.01 |
peak threads |
382 threads |
379 threads |
1.01 |
network (transport) |
2725.832 MB |
2727.928 MB |
1.00 |
disk write |
1.613 MB |
1.93 MB |
0.84 |
instructions |
137.299 G |
138.562 G |
0.99 |
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Three ABC Sim (amazon-far/abc) scenes, each its own LFS archive: count into a lidded box, grab from clutter, and put-relative. One YAM arm does the task and the other stays parked. - abc_yam: planning URDF generated from ABC's YAM MJCF, so planner and sim share the same kinematics (the i2rt URDF is up to ~1.2 cm off). - openyam-manipulation-sim: ManipulationModule + skills on the sim_mujoco adapter, with ABC's fixed overhead camera. - abc_sim suite with count_inside and placed_beside graders, following abc_sim/task_eval.
One LFS archive per ABC Sim scene (env_task), abc_<env_task>, 20 in all, built from amazon-far/abc @ d0832d1 XML and asset files only (ABC's Python is not run). Both YAM arms stay active: ABC's 14 position actuators, in its own order, are what MujocoSimModule drives with dof=14. - abc_yam: dual_yam.urdf (two arms on ABC's mount, 5e-9 m grasp-site error vs the MJCF) and every arm mesh, which the scenes load from ../abc_yam/meshes. - Fixed layouts: ABC's templates; put_bottles, dishrack and inhand_transfer are filled with ABC's default variants at its nominal spots; six chess pieces start off the board; the building-blocks L block no longer starts inside the table; the conveyor belt does not move (ABC drives it from Python). - Physics step as in abc_sim/task_registry.py (0.5 ms pour, 0.2 ms drawer). See data/abc_yam/SOURCE.md.
dual-openyam-abc-sim drives both simulated YAM arms in an ABC scene (data/abc_<task>): one planning group per arm (left_manipulator, right_manipulator) on abc_yam/dual_yam.urdf, one 14-joint sim_mujoco device (arm/left_joint1..6, arm/left_gripper, then the right arm), one trajectory task for both arms and a gripper task per jaw. The sim adapter reports every joint as +-pi, so the device declares ABC's joint ranges and each gripper's finger travel (0 closed, 0.0475 m open). The camera is ABC's fixed overhead "top" camera. AbcScenePath pulls abc_yam along with a scene, since the scenes load their arm meshes from it.
Graders on recorded body poses that follow abc_sim/task_eval: in_box (items in a container's region, others kept out), in_cylinder (beads in a cup, mugs on a mug tree), upright and standing (mugs flipped and at rest, plates on edge), spelled (letter cubes in reading order), set_up (chess pieces back on their squares, identical pieces interchangeable), crossed_table (in-hand transfer), held_on_tray, tower, and all_of to combine them. held_on_tray is stricter than ABC's ball-tray evaluator, which passes a robot that never moves: the tray must stay lifted with the ball on it for the last 10 s. ABC has no evaluator for its wood-block tower; tower is ours.
dimos.evals.suites.abc_sim now has one case per ABC task spec (abc_sim/task_specs.py), abc_<spec name>, each in its ABC scene on dual-openyam-abc-sim and graded on recorded body poses. Cases are tagged with the ABC scene, the task family, and dual_arm (24) or single_arm (9). Departures from ABC, all tagged or documented in the suite: fixed layouts and object-naming prompts instead of randomized episodes; a still conveyor belt (static_belt); a stricter ball-tray grade; our own graders for the three marker drawers and the wood-block tower (ours_grader). The three single-arm cases move to dimos.evals.suites.abc_sim_single_arm. Like the other manipulation suites, both drive the arms through the Python API instead of an MCP server.
…ompts Both OpenYAM sim blueprints gain HeuristicGraspModule. The cases drop observe-skill and the no-op disable list, give the task plus a one-line note on the modules instead of table heights and frames, and let localize confirm an object from one view, as the overhead camera never moves.
…able grasp timestamp error
Sim feedback at -1.5708074 against a -1.5708 limit made Pink IK and RoboPlan reject every start state.
…agent remote_hidden_rpcs leaves them out of list_modules, so the porcelain client cannot call them; the coordinator still calls scene_path in-process.
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…os agent - NVIDIA EGL vendor file and graphics capability, for MUJOCO_GL=egl. - Chromium through npx: the deno playwright install stalls after the download. - web/sdk and web/shared in the build context, which the dimos agent build reads.
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Problem
There are no ABC Sim tasks in the evals.
Changes
data/.lfs/abc_*.tar.gz).openyam-manipulation-sim(one arm) anddual-openyam-abc-sim(both arms) blueprints.abc_sim: all 33 ABC tasks, both OpenYAM arms.abc_sim_single_arm: 3 tasks, one arm.dimos/evals/scorers.py.manipulation-localize, and get grasps from the heuristic grasp module.peek_streamrefusesbody_poses.reset,respawn_atorscene_path(remote_hidden_rpcs).data/and the MuJoCo model.Testing