SmartFollower & Tracker (SFT) for Warehouse Anomaly Investigation

Mission Statement: Design and implement an indoor TurtleBot 4–based autonomous system that can detect, track, and safely follow a designated Object of Interest (OOI) through a dynamic warehouse/packaging environment, while circumventing obstacles and producing a 2D reconstruction (map + trajectory + time-stamped evidence) for anomaly investigation and audit.

1. Mission Statement & Scope

1.1 Operational Motivation

Warehouses routinely experience exception events (e.g., missing package in a tote/pallet, misrouted items). The SmartFollower & Tracker (SFT) provides a mobile “investigation and tracking” that can follow ArUco-tagged OOI, navigate around obstacles, and generate a 2D reconstruction with evidence logs to support rapid verification and root-cause analysis.

1.2 Target Environment

Primary environment: Indoor warehouse / factory logistics zones (no GPS), including:

  • Aisles & staging areas: narrow aisles, pallet stacks, shelving occlusions
  • Packaging zones: dense clutter, human traffic, carts, reflective floors
  • Loading-bay edges + truck interiors (optional test zone): illumination changes, confined geometry, ramps/thresholds

Key constraints:

  • Dynamic obstacles (workers, carts, pallets)
  • Dynamic targets with ArUco attached
  • Frequent occlusions and lighting variability
  • Safety requirements for shared human-robot space
  • Narrow spaces for robot to pass through

1.3 Primary Problem Statement

Given a dynamic indoor warehouse environment without GPS, develop a mobile robot system that:

  1. Acquires an OOI using onboard sensors
  2. Tracks the OOI robustly (including temporary occlusions)
  3. Follows/chases while maintaining safety constraints (distance, speed limits, collision avoidance)
  4. Reacquires the OOI after loss or transitions to safe fallback behavior
  5. Produces a 2D map + trajectory + time-stamped observations usable for anomaly investigation

1.4 Scope

  • TurtleBot 4 autonomy
  • ArUco-based OOI detection and tracking
  • Dynamic objects & Static objects tracking
  • Smart following control (distance/heading regulation)
  • Local obstacle avoidance & optional global planning
  • 2D reconstruction & evidence logs

1.5 Success State (Measurable Acceptance Criteria)

Baseline success criteria (must be met in representative indoor test runs):

  1. OOI acquisition: detect OOI within ≤ 3 s after entering sensor FOV
  2. Tracking continuity: maintain track ≥ 90% over a 5-minute run with ≥ 3 occlusion events
  3. Reacquisition: reacquire within ≤ 5 s after temporary loss, else trigger safe fallback
  4. Following performance: maintain follow distance 1.0 m ± 0.3 m (configurable)
  5. Safety outcome: zero collisions; robot slows/stops and routes around obstacles within a defined safety radius
  6. 2D reconstruction output: export (i) occupancy map and (ii) trajectory + time-stamped OOI detection log

1.6 Assumptions & Constraints

  • Flat indoor ground; ramps/thresholds allowed only within platform capability
  • Network may be intermittent; autonomy must degrade safely
  • Embedded compute limits may constrain perception throughput; document any offboard compute if used
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