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RobotParticleForensics

A self-directed robotics R&D project: a mobile particle-forensics robot — a UR5e-class cobot on a linear rail, carrying an inspection head with UV illumination and multi-modal cameras. It reaches into enclosed precision equipment, images fine particle distributions, and uses a vision + LLM-agent pipeline to help localise where contamination is coming from.

Two perception jobs run at once:

  • Inspection eyes — high-magnification UV/2D imaging → particle detection, size distribution, spatial mapping onto a reference frame.
  • Guiding eyes — a wrist-mounted depth camera → voxel map → collision-aware motion planning for safe entry into tight spaces.

The LLM agent is a collaborator, not an autopilot: a human describes the symptom, the agent proposes an inspection sequence, executes it behind confirm-gates, presents image evidence, and iterates.


What's here right now

The simulation work is the live part of this repo — everything runs on a laptop, no hardware required.

Doc Phase What it covers
00_Simulation_Roadmap.md Master roadmap: phases, sim-engine tradeoffs, what the sim can and cannot prove
01_Phase1_UR5e_URScript.md 1 ✅ UR5e moving via real URScript through URSim's actual PolyScope controller, plus MoveIt2 planning and Gazebo visualisation
02_Phase2_Linear_Rail.md 2 ✅ The rail as a true 7th DOF in one kinematic chain — one IK solution, one trajectory, one execution
02b_OvalRail_Custom_Kinematics_Plugin.md 2 Why a custom closed-loop kinematics plugin was evaluated and rejected
02c_Planning_Stack_Concepts.md 2 How the MoveIt planning stack actually fits together
02_Setup_Sequences_and_Troubleshooting.md Bring-up sequences and the failure modes hit along the way

Code:

A standalone reference on the robot communication stack: UR's eight native control and integration interfaces, and what ROS 2 actually buys you over a raw TCP socket.


Roadmap

Phase Goal Status
1 UR5e in sim, driven by real URScript and by MoveIt2 ✅ Done
2 Linear rail as a 7th DOF, single coordinated trajectory ✅ Done
3 Inspection-tool mockup in scene as a collision object; scripted inspection sweep 📋 Planned
4 Perception — UV/2D particle detection + depth → occupancy feeding the MoveIt collision scene 📋 Planned
5 Agent layer — natural-language symptom → bounded inspection sequence, human confirm-gates, structured evidence report 📋 Planned
6 Integration, cheap physical surrogate, demo video and write-ups 📋 Planned

Stack

ROS 2 Jazzy · MoveIt 2 · Gazebo (Isaac Sim targeted for vision-in-the-loop) · URSim / PolyScope · URScript · Python · WSL2 on Windows 11

Goals

  1. Learn robotics for real — motion planning, kinematics, coordinate frames, EOAT design, sim-to-real workflow.
  2. Build genuine perception pipelines — 2D + 3D detection, segmentation, depth → occupancy. Not slideware.
  3. Practice agentic AI on hardware — an LLM agent wired to a bounded, safe action executor with human-in-the-loop gates.
  4. Produce a portfolio-grade artifact — clean repo, reproducible build, real demos, honest write-ups of what worked and what didn't.

A note on CDR references

Several docs reference a CDR (Critical Design Review) and its slides. That design review is the project's architecture record; the deck itself is kept privately and is not published in this repository. The references are retained because the reasoning they point at is genuine design history — treat them as pointers to an internal record, not a broken link.

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