Research: exhaustive Nimso Project TX study (82 video transcripts) + Boneworks/BIMOS rig reference

- research/nimso-project-tx.md: chronological per-video notes 2017-2026, topic synthesis,
  VR Messs scope, proportions & calibration (Winter/Drillis-Contini/Dempster tables verified),
  open unknowns
- research/sources/nimso-transcripts/: yt-dlp auto-caption transcripts + dated index (re-pullable)
- research/vr-physics-rig-hexabody.md: BIMOS/HexaBody/Boneworks reference, Box3D native joint
  mapping (spherical/motor/prismatic/distance), superseded-as-target note
- AGENTS/HANDOFF research pointers

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

research/sources/nimso-transcripts/lHgpibsjgek.txt

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+# FLUID VR HAND ADAPTATION + Hand Tracking - HYBRID PRESENCE ENGINE (lHgpibsjgek, 1202s)
+
+[Music] it's me n so welcome back to another VR video today we are back in Project TX well at least the makings of project TX kind of be behind the scenes stuff um we are for the first time in a video properly in a proper video I'm looking through a Quest 2 connected on link even though this build will be compatible with PC and Quest when it when it's built um that's for a reason and you will have figured that out pretty quickly uh as well before I actually use it but right now today's video we are looking at something a little bit more advanced than my usual stuff it's a new system uh it's a new system that repl place is an old one um and what I've been doing recently is I've been rearranging a lot of my cord um a lot of my old cord um kind of the the entire hybrid presence engine I'm calling it hybrid presence engine now uh because system doesn't really cover what it does it does everything from tracking to the body physics to the body pausing the elbow ik it's not really ik but it's ik it's inverse kinematic you know at a logical level uh it does all of that thing that stuff the the whole gameplay mechanics and everything and it's all modular and uh that's the new sort of layout is is completely modular it works really really well what we're looking at today though is what you've been looking at this whole time as well which is the new hand pausing system uh this is something I'm calling the fluid hand pause system uh you will have uh my words have just completely died there uh you will have played a game called Born lab uh recently in the past year or you may have at least seen it if you're a VR Enthusiast and uh in that game one of the new systems they' kind of built was the idea of avatars that you can retarget your natural body to match the Avatar's uh sort of structure to try and keep the avatars with their own natural structure rather than retargeting them to make them shaped like Q so for example here with my regular physics hands I could switch to longer arms and you can see that they kind of match my same uh my my natural arm when when my arm is at full extension my my arm is at full extension in the game even if it's longer so here we go regular hand and now for the longer one and it's it's matching that right so same thing as you would see in that game and it's full physics right so there we go but I thought I wanted to take that idea and I wanted to do it for something that you wouldn't really expect to do it for hands hand pausing so the finger posing that you're seeing here let's go back to a regular hand so it matches mine the finger posing that you're seeing here is not built in the way that normal finger pausing systems are built where you have data specifically oh no let's give me a sec sorry about that uh what happens when you tap the controls I'll show you that in a minute um when you have each finger in a regular in regular hand pause system you have each finger as actual data points inside the system and uh they kind of pulled in you kind of set your finger to a certain pae and you apply that to your character model in this system I'm not really doing that it's a little bit more complex in in terms of data I call this the fluid hand pause system and the reason being that I'm not storing specific finger pause data rather it's just sort of a blend right across the board and it doesn't actually care how many fingers you have which is very very unusual in in fact it doesn't even care how many segments you have either so here you've got 1 2 three you've got three segments on each finger um but it doesn't actually care about that that stuff is not part of the system it doesn't have dedicated finger data for each of the fingers right which means you can take these regular poses so here's my my regular poses there's only four pauses in my entire system right which is uh open hand uh grip trigger index trigger and then both triggers right that's that's all of the pauses right and of course then there's the touch sensor data that comes in and and adapts to that and adapt is the very uh is the important it's the word of the day today right uh a word of the night evening it's past 12 it's morning but there we go so what this means is because it doesn't care how many fingers I have on the hand it just it just has the same poses I can switch to different hands so here we go so now I've got three fingers and a thumb on each hand and these pauses are the same four paes that I was using just now it's the same data literally the same data it's all just coming in and applying to the character model now of course you're probably thinking okay well that's very simple you've got three fingers you can just cut one out and and and only use the data from one of them uh uh only only use the data from one of them only use the data from three of them instead of all four that's not what's actually happening you can see here each finger has a different pae right which makes sense because you only have three youLine truncated