Mermaid musings: simple graphs of actors

Miscellaneous
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After watching the first part of Jeff’s video How Embodied Movements Might be Learned and Controlled, I decided it would be fun, interesting, and possibly useful to recast Jeff’s diagrams in the pattern I’ve been experimenting with in this thread.

Recasting Hearing as Vision

Because Jeff’s presentation concerns vision rather than hearing, we need to recast our last diagram a bit, as:

graph LR;
  AM_MM["Asst. Monty<br>(LM)"]
  DB_SA["Dashboard<br>(SA)"]
  SC_SA["System Clock<br>(SA)"]
  EP_MM["Eye Position<br>(MM)"]
  LE_SH["Left Eye<br>Sensors<br>(SH)"];
  LE_LH["Left Eye<br>(LH)"];
  LE_SM["Left Eye<br>(SM)"];
  RE_SH["Right Eye<br>Sensors<br>(SH)"];
  RE_LH["Right Eye<br>(LH)"];
  RE_SM["Right Eye<br>(SM)"]
  BV_LM["Binocular and<br>Stereo Vision<br>(LM)"]

  DB_SA <-- GQL --> BV_LM;
  SC_SA -- NTP --> BV_LM;

  LE_SH -- Raw --> LE_SM;
  LE_SH -- Raw --> LE_LH;
  RE_SH -- Raw --> RE_SM;
  RE_SH -- Raw --> RE_LH;
  
  LE_LH <-- MCP --> BV_LM;
  RE_LH <-- MCP --> BV_LM;
 
  LE_SM <-- CMP --> BV_LM;
  RE_SM <-- CMP --> BV_LM;
  
  BV_LM <-- CMP --> AM_MM;
  BV_LM -- CMP --> EP_MM;

Legend

  • Edge Types

    • CMP: CMP data structures, embedded in MCP
    • GQL: GraphQL data structures, embedded in MCP
    • MCP: other data structures, embedded in MCP
    • NTP: NTP data structures, embedded in MCP
    • Raw: raw analog or digital data

  • Node Types

    • LH: LLM-based harness
    • LM: Learning Module
    • MM: Motor Module
    • SA: Support Actor
    • SH: Sensor Hardware
    • SM: Sensor Module

Digital Cameras vs. Eyes, etc.

Just as microphones aren’t ears, digital cameras aren’t eyes. Even a “simple” RGB CCD array is quite different from a retina. Fold in the things needed to provide an RGBD camera with depth information (e.g., stereo vision, structured light, time of flight sensing) and things quickly get very far from biological practices.

Fortunately, we can skip over these differences, while noting that there are going to be obvious similarities in the results (e.g., color vision, depth perception, non-linear intensity scaling) we’d like Monty to achieve.

We can also leave out the Dashboard, LLM-based harnesses, and System Clock, making room for more details in other aspects of the sketch (e.g., Drivers). But that will have to wait for the next installment…

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