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Compatibility Matrix

The matrix below shows which robot category each task supports. A ✓ marks a supported combination; a blank cell means it is not available. Tasks prefixed with _ (e.g. _manipulation) are reusable base templates rather than directly runnable scenarios.

Scope. This matrix is about robot categories only. A ✓ says a task accepts robots of that category; it does not say that the task is solved, that any learner has been validated on it, or that it has been run on physical hardware. Learner and hardware readiness are tracked separately — see the note below the table.

TaskManipulatorMobile ManipulatorMobile Robot
lunalab
zerog_lab
_manipulation
debris_capture
excavation
excavation_demo
modular_assembly
multi_peg_in_hole
multi_sample_collection
peg_in_hole
sample_collection
screwdriving
solar_panel_assembly
_aerial
_ground
_orbital
aerial_navigation
beam_transport
flight
formation_following
formation_following_decentralized
formation_following_orbital
landing
locomotion_velocity_tracking
locomotion_waypoint_navigation
moonfall
orbital_evasion
orbital_waypoint_navigation
rendezvous
terrain_landscaping
terrain_landscaping_crater
terrain_landscaping_mound
traversal
velocity_tracking
waypoint_navigation
_aerial_manipulation
_ground_manipulation
_orbital_manipulation
mobile_debris_capture
spacewalk
spacewalk_eva
spacewalk_iva

What this table does not say

A row in this matrix is not a support claim for any learner or for physical hardware.

For the terrain landscaping tasks specifically, the measured state is:

terrain_landscaping_craterterrain_landscaping
Dreamer integration runs one environment end to endyes, with a reliability caveatnot measured
Dreamer learnability demonstratedno — the gate could not be measuredno
TD-MPC2 supportedno — disabled, fails closedno — disabled, fails closed
Batched training (env.num_envs > 1)no — refused fail-closedno
Environment reachability by a scripted referencenono
Real-hardware validationnone existsnone exists

Both landscaping rows above are blank in the matrix itself. That is the honest reading: neither task is offered as a solved, learner-validated, or deployable scenario. See Terrain Landscaping Training Readiness for the gate-by-gate detail and docs/superpowers/evidence/terrain_landscaping/readiness.json for the machine-readable report.