This paper presents a novel method for the timeoptimal rendezvous of an autonomous vehicle with moving targets in the presence of dynamic obstacles. This interception problem is addressed by utilizing the velocity obstacle approach of Fiorni and Shiller augmented with a rendezvousguidance algorithm. However, the velocity obstacle approach had to be modified to ensure that the real-time planned path deviates minimally from the one generated by the rendezvousguidance algorithm. Simulation and experimental results, some of which are presented in this paper, clearly demonstrate the efficiency of the proposed interception method.
Biofouling is an unwelcomed phenomenon where unwanted biological matter adheres to surfaces with the presence of water, resulting in alteration to the properties of the surface. This affects many industries, especially the marine industry. Multiple biofouling control studies have been conducted to minimize damage and maintenance cost of these surfaces. With rising concerns on the toxicity of current control methods towards the environment, non-toxic methods shown to be effective are surface modifications such as self-cleaning or biomimetic textured surfaces. One of the biomimetic surfaces, shark’s skin has shown anti-fouling properties due to its surface riblets with low drag properties based on studies done. However, few researches are conducted to implement these biomimetic surface topographies for real anti-fouling applications. Therefore, this project explores the possibilities in implementing biomimetic surface topographies such as shark’s skin in real life applications using computational fluid dynamics (CFD) analysis and also to manufacture these surfaces using 3D printing methods. A computer-aided design (CAD) model of shark skin and un-patterned surface topographies are used to study the behavior of fluid over these surfaces in CFD fluent in ANSYS software. The hydrodynamic variable data such as wall shear stress over the surface topography is represented in a contour and vector plot, these results are then analyzed. According to the hypotheses, the biomimetic shark skin surface topography will show higher wall shear stress, indicating anti-fouling properties. In the next part of this project is the manufacturing of these surface, the goal is to provide a cheaper alternative to current micro-structured surface production methods such as photolithography. Additive manufacturing such as fused deposition modeling (FDM) 3D printing can potentially provide a manufacturing method with a much lower cost and time needed. Thus, 3D printing of the biomimetic shark skin surface topography will be carried out in this project to determine if FDM can provide a manufacturing solution to anti-fouling micro-topography surfaces.
Obstacle avoidance and navigation (OAN) algorithms typically employ offline or online methods. The former is fast but requires knowledge of a global map, while the latter is usually more computationally heavy in explicit solution methods, or is lacking in configurability in the form of artificial intelligence (AI) enabled agents. In order for OAN algorithms to be brought to mass produced robots, more specifically for multirotor unmanned aerial vehicles (UAVs), the computational requirement of these algorithms must be brought low enough such that its computation can be done entirely onboard a companion computer, while being flexible enough to function without a prior map, as is the case of most real life scenarios. In this paper, a highly configurable algorithm, dubbed Closest Obstacle Avoidance and A* (COAA*), that is lightweight enough to run on the companion computer of the UAV is proposed. This algorithm frees up from the conventional drawbacks of offline and online OAN algorithms, while having guaranteed convergence to a global minimum. The algorithms have been successfully implemented on the Heavy Lift Experimental (HLX) UAV of the Autonomous Robots Research Cluster in Taylor’s University, and the simulated results match the real results sufficiently to show that the algorithm has potential for widespread implementation.
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