This paper introduces a motion planning approach for navigating in a dynamic environment. The path is represented using a Non-Uniform Rational B-Spline (NURBS) to ensure smoothness, curvature continuity, and proper orientation by adjusting its parameters. A Differential Evolution algorithm optimizes the curve parameters and traversal speed at each replanning interval, taking into account speed limits, maximum curvature, and obstacles in the environment. A constraintbased on Velocity Obstacle (VO) ensures collision-free motion, considering bounds provided by lower-level controllers. The feasibility of the approach is validated through simulations and real-world experiments with the Crazyflie 2.1 micro quadcopter.

Spatial tracking in Mixed Reality (MR) relies on the device's sensor fusion and localization accuracy, directly impacting virtual object placement and user interaction. In this paper, we measure the minimum achievable projection error of Microsoft's HL2 with an industrial-grade robotic manipulator as ground truth. Specifically, we use a reproducible methodology to measure the device's highest achievable spatial accuracy and precision under controlled motion trajectories and tracking scenarios, including static positioning, sinusoidal 1D dynamic motions, and circular 2D planar movements at varying tangential velocities. Additionally, we investigated the contribution of different device sensors to overall positioning error by manually blocking specific sensor inputs. The analysis revealed an average localization error of approximately 5 mm with a standard deviation of 5.5 mm, representing the device's accuracy and precision, respectively. The goal is to provide realistic expectations of MR readiness levels with respect to its highest achievable accuracy and precision, shedding light on its capabilities and limitations for different applications.