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Mapping a desired 2D pattern onto a curved surface has many applications. This includes motion planning for mobile robots to perform coverage path planing, robot end effector trajectory design for tasks such as printing, depositing, wielding on a 3D surface. This problem becomes more difficult if we want the mapped pattern to keep the properties of the original pattern (i.e, least possible mapping distortion), and pass over some desired points and/or remain bounded in a specific region on the surface. In this paper, we apply surface parameterization and mapping distortion analysis, which is rarely used in robot motion planning works, to map a pattern onto 3D surface. To meet additional goals such as passing over certain points, a planar mapping determined by constrained optimization is employed on the original pattern. Our focus is on printing/depositing materials on curved surfaces, and simulations and experiments are provided to confirm the performance of the approach. 

Skin surface wounds due to burns, surgeries and chronic illness affect millions of people worldwide. Tissue engineering has become an increasingly popular treatment, but it is a highly manual process. Increasing the automation in tissue engineering could increase the rate of treatment for patients and improve outcomes. We present an initial investigation into an automated in-situ treatment. In our proposed method, a 3D machine vision system detects a skin wound to be treated and then determines the 3D point set corresponding to the wound. The 3D point set is then passed to path planning algorithm for a robot manipulator to move an ink-jet nozzle over the wound and fill the cavity with quick-curing/gelling fluids such collagen and other biomaterials and cell growth promoters. This paper details initial results and experimental validation of each of the proposed steps. 

In the field of inkjet deposition, there is a lack of specific knowledge to detect and change drop volume to regulate fluid placement. In this paper, we present a novel control scheme to regulate drop diameter on a surface with unknown properties. We derive a model for line width as a function of nozzle velocity, valve duty cycle, and physical properties of fluid and surface. As many of these variables are generally unknown, we present a nonlinear estimator to estimate their cumulative effects as a single variable. Next, benefiting from our estimation knowledge, a closed-loop control method is designed to track a time-varying line width. Stability of both the estimator and control are established using Lyapunov stability theory, and the control is shown to be robust to errors in the estimator. Simulations and experimental results confirm the stability and performance of the approach.