AMD Physical AI for embodied household manipulation
A complete workflow from data and training to closed-loop evaluation, anchored by the RoboCasa365 household benchmark and extended through DexJoCo dexterity, DISCOVERSE simulation, and PAC-MAN whole-body safety control.
RoboCasa365 official policies on AMD
Official Pi0.5 and GR00T checkpoints complete the same 16-task closed-loop evaluation on the AMD Ryzen AI MAX+ 395. Each model runs 800 formal episodes with per-task results and synchronized four-view video.
AMD Physical AI in motion
From DexJoCo dexterous manipulation and RoboCasa365 household tasks to DISCOVERSE multi-view replay and PAC-MAN safety control, the film shows one AMD workflow across multiple robot capabilities.
Seven complementary evidence tracks
From a teaching baseline to multi-simulator, benchmark, creative-operation, and hardware evidence.
RoboCasa365 · 16 tasks
Official Pi0.5 and GR00T checkpoints run the same 16-task, 50-episode closed-loop protocol on the AMD 395 with per-task statistics and four-view video.
- tasks
- 16
- episodes
- 50 / task
- video
- 4-view
DISCOVERSE · full-stack migration
Official scenes, expert trajectories, policy entry points, closed-loop evaluation, HD multi-view replay, and MP4 export form a complete migration path from simulation to visual evidence.
- Runtime
- 18 / 18
- AIRBOT
- 12 / 12
- Expert data
- 500 eps
PAC-MAN · perceptive CBF-RL
The upstream dodge_link_cbf ONNX policy fuses four depth-history frames with G1 proprioception. The robot holds its stance, then autonomously selects a duck, left sidestep, or right sidestep when the ball enters view.
- observation
- 960-D
- modes
- 3 / 3
- video
- 1080p
DexJoCo · Pi0.5 native JAX
Official Orbax weights run natively with AMD ROCm JAX 0.10 across bimanual coordination, tool use, precision grasping, and long-horizon contact tasks, creating a multi-task Pi0.5 dexterous-manipulation showcase.
- tasks
- 11
- runtime
- JAX 0.10
- media
- 10+ videos
AMD dual-device lab
The local Ryzen AI MAX+ 395 runs sustained evaluation while the cloud Radeon Pro W7900 handles high-memory training and migration validation.
- AMD 395
- RoboCasa
- W7900
- VLA + ACT
- stack
- PyTorch + JAX
Public result JSON, training checkpoints, HD video, and reproduction guides are indexed by workstream.
RoboCasa365 matched task benchmark
| Task | GR00T | Pi0.5 | Delta |
|---|---|---|---|
| Loading verified results… | |||
GR00T long-horizon success showcase
GR00T N1.5 multi-task weights on the AMD 395 complete restocking and meal-packing sequences in household scenes, with four synchronized camera views for every trace.
Restock task · successful trace
Meal-packing task · successful trace
Four synchronized views reveal robot motion, wrist detail, and environment state throughout each long-horizon household task.
DISCOVERSE HD three-view replay
The same AMD-migrated MMK2 expert state machine; each showcase includes native 1920×1080 cam_0, cam_1, and cam_2 recordings composed into one three-view canvas.
Box pick · strict success
Drawer open · strict success
Cabinet door open · strict success
Cup to plate · strict success
Three synchronized views capture the workspace, end-effector detail, and environment state on one replay timeline.
Real Gaussian Splatting rendering on ROCm
The ROCm Gaussian renderer combines point assets, camera motion, lighting, and robot replay into a visual layer for the migrated scenes.

640×360
640×360Dynamic replay: Franka and UR5e
Two renderer targets, two non-empty validation frames, and two dynamic films demonstrate the ROCm Gaussian Splatting path; the DISCOVERSE expert films connect rendering to robot task execution.
Success cases
water_plant · seed 0 success
06_dominos · episode 1 success · 848×480
In-place whole-body dodging
Red-cup strict success
CloseFridge success · 1920×1080
DrawerToCounter success
Block bridge · strict replay
Pi0.5 success case archive
Official multi-task weights run on AMD ROCm JAX 0.10 across 11 dexterous manipulation tasks. The page presents task videos covering bimanual coordination, tool use, precision grasping, and long-horizon contact, with the complete task map and result JSON archived alongside them.
Bimanual coordination, tool use, precision grasping, and long-contact tasks form the complete task family.
Official Orbax weights run natively on AMD ROCm, with video and JSON produced by one evaluation entry point.
The gallery presents bimanual motion, precision contact, tool use, and deterministic success-seed replays.
| Task | Capability | Task media |
|---|---|---|
| bimanual_assembly | two-hand assembly | View task |
| bimanual_hanoi | long-horizon placement | View task |
| bimanual_microwave_cook | tool + contact coordination | View task |
| bimanual_photograph | precision pose control | View task |
| click_mouse | fine manipulation | View official demo |
| fold_glasses | deformable object handling | View official demo |
| hammer_nail | tool use | View official demo |
| pick_bucket | grasp and lift | View official demo |
| pinch_tongs | precision pinch | View official demo |
| water_plant | pouring and release | View task |
Bimanual coordination, tool use, and precision grasping
One auditable loop
- 01SimulationRoboCasa · MuJoCo · DISCOVERSE
- 02Datafixed seed · LeRobot · audit
- 03AMD trainingSmolVLA · Pi0.5 · GR00T · ACT
- 04Closed-loop evaldenominator · success/failure videos
- 05EvidenceJSON · SHA256 · checkpoint
Training
The public tutorial provides runnable notebooks, protected weights, configs, strict evaluation summaries, and SHA256 records.
Failure cases
Boundary-case replays expose policy behavior across navigation, approach, contact, grasp, and placement with synchronized visual evidence.