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Autonomous Drone LiDAR Obstacle Clearance (Computer Engineering)

In autonomous robotics and unmanned aerial vehicle (UAV) guidance systems, real-time path planning algorithms must compute the minimum clearance distance between a drone's programmed flight trajectory and physical obstacles detected by onboard LiDAR point clouds.

A computer engineering team programs an autonomous surveillance drone executing an inspection survey over a power substation. In a local coordinate system (scaled in decameters, where 1 dam=10 meters1\text{ dam} = 10\text{ meters}), the drone follows a pre-computed quadratic ascent path modeled by:

y=0.5x2for x∈[−4,4]y = 0.5x^2 \quad \text{for } x \in [-4, 4]

The drone's forward-looking solid-state LiDAR sensor detects an unmapped high-voltage transmission pylon located at coordinate point P(0,4)P(0, 4). The drone's collision-avoidance firmware requires calculating the closest point of approach (CPA) and the absolute minimum clearance distance between the flight path and the pylon to determine if a trajectory replanning interrupt must be triggered (threshold clearance: dmin⁡≥2.0 damd_{\min} \ge 2.0\text{ dam}).

                          y ^
                            |      P(0, 4) [Pylon]
                            |        o
                            |       / \
                            |  d   /   \
                            |     /     \
                            |    v       v
                            |   *         * [Closest Points]
                            |  /           \
                            | /  y = 0.5x^2 \
                            +-------------------> x
  1. Formulate the Euclidean distance function d(x)d(x) between the pylon at (0,4)(0, 4) and an arbitrary point (x,y)(x, y) on the flight trajectory.
  2. Apply the Squared-Distance Optimization Technique to define the simplified single-variable objective function D(x)=[d(x)]2D(x) = [d(x)]^2.
  3. Differentiate D(x)D(x) to locate all critical numbers of the distance function along the flight corridor x∈[−4,4]x \in [-4, 4].
  4. Classify each critical point using the Second Derivative Test, identifying whether each represents a local maximum or local minimum clearance.
  5. Compute the coordinates of the closest approach points and the absolute minimum clearance distance dmin⁡d_{\min} (in decameters and meters). Does the drone satisfy the 2.0-dam2.0\text{-dam} safety margin?