Determining how to assemble a meal

1. A method comprising:

determining a given material to manipulate with an end effector of one or more autonomous robots to achieve a goal state, the goal state being one or more deformable or granular materials in a geometric distribution;

for the given material, simulating a respective simulated geometric distribution for each of a plurality of candidate actions performed by the end effector of the one or more autonomous robots to manipulate the given material;

selecting a given action of the candidate actions based on the respective simulated geometric distribution of the selected given action having a closest geometric distribution of the goal state;

based on the selected given action, generating a first motion plan for the one or more autonomous robots to execute the selected given action; and

executing the first motion plan using the one or more autonomous robots.

2. The method of claim 1 , further comprising:

creating a new goal state having the given material manipulated;

determining a new given material to manipulate to achieve a new goal state, the new goal state being one or more deformable or granular materials including the given material in a particular arrangement;

for the new given material, simulating a respective simulated geometric distribution for each of a plurality of new candidate actions to manipulate the new given material;

selecting a given new action of the new candidate actions based on the respective simulated geometric distribution of the new given action having a closest geometric distribution of the new goal state; and

based on the new selected given action, generating a second motion plan for the new selected given action.

3. The method of claim 2 , further comprising:

ordering, for execution, the first motion plan and second motion plan based on one or more rules, wherein the rules include one or more of material based rules, ease of assembly rules, and parallelization rules, said ordering resulting in an order.

4. The method of claim 3 , further comprising:

executing the first motion plan and second motion plan in the order using one or more autonomous robots.

5. The method of claim 4 , wherein a first autonomous robot of the one or more autonomous robots executes the first motion plan and a second autonomous robot of the one or more autonomous robots executes the second motion plan.

6. The method of claim 3 , wherein ordering is based on at least one of:

one or more instructions of ingredients or actions;

a set of material rules;

predicted based on a physics-based model, and

a heuristic.

7. The method of claim 1 , wherein determining a given action of the candidate actions includes one or more of:

adding the given material to the goal state;

removing a given material from an existing state; and

performing a process step to the given material and one or more other materials.

8. A system comprising:

a processor; and

a memory with computer code instructions stored thereon, the processor and the memory, with the computer code instructions, being configured to cause the system to:

determine a given material to manipulate with an end effector of one or more autonomous robots to achieve a goal state, the goal state being one or more deformable or granular materials in a geometric distribution;

for the given material, simulate a respective simulated geometric distribution for each of a plurality of candidate actions performed by the end effector of the one or more autonomous robots to manipulate the given material;

selecting a given action of the candidate actions based on the respective simulated geometric distribution of the selected given action having a closest geometric distribution of the goal state;

based on the selected given action of the given one or more actions, generate a first motion plan for the one or more autonomous robots to execute selected action; and

executing the first motion plan using one or more autonomous robots.

9. The system of claim 8 , wherein the instructions further cause the processor to:

create a new goal state having the given material manipulated;

determine a new given material to manipulate to achieve a new goal state, the new goal state being one or more deformable or granular materials including the given material in a particular arrangement;

for the new given material, simulate, with a physics-based simulator, a respective simulated geometric distribution of new candidate actions to manipulate the new given material;

select a given new action of the candidate actions based on the respective simulated geometric distribution of the given new action reaching the new goal state;

based on a new selected action, generate a second motion plan for the new selected action.

10. The system of claim 9 , wherein the instructions further cause the processor to:

order, for execution, the first motion plan and second motion plan based on one or more rules, wherein the rules include one or more of material based rules, ease of assembly rules, and parallelization rules, said ordering resulting in an order.

11. The system of claim 10 , wherein the instructions further cause the processor to:

execute the first motion plan and second motion plan in the order using one or more autonomous robots.

12. The system of claim 11 , wherein a first autonomous of the one or more autonomous robot executes the first motion plan and a second autonomous robot of the one or more autonomous robots executes the second motion plan.

13. The system of claim 10 , wherein ordering is based on one or more instructions of ingredients or actions.

14. The system of claim 8 , wherein determining a given action of the candidate actions includes one or more of:

adding the given material to the goal state; and

performing a process step to the given material and one or more other materials.