Browsing by Author "Huang, Li"
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Item Efficient Parallel Self- Assembly Under Uniform Control Inputs(IEEE Robotics and Automation Letters, 7/9/2018) Becker, Aaron T.; Schmidt, Arne; Manzoor, Sheryl; Huang, Li; Fekete, Sándor P.We prove that by successively combining subassemblies, we can achieve sublinear construction times for “staged” assembly of microscale objects from a large number of tiny particles, for vast classes of shapes; this is a significant advance in the context of programmable matter and self-assembly for building high-yield microfactories. The underlying model has particles moving under the influence of uniform external forces until they hit an obstacle; particles bond when forced together with a compatible particle. Previous work considered sequential composition of objects, resulting in construction time that is linear in the number N of particles, which is inefficient for large N. Our progress implies critical speedup for constructible shapes; for convex polyominoes, even a constant construction time is possible. We also show that our construction process can be used for pipelining, resulting in an amortized constant production time.Item Towards Microrobot Swarm Path Planning(2019-08) Huang, Li; Becker, Aaron T.; Claydon, Frank J.; Mayerich, David; Nguyen, Hien Van; Lindner, PeggyTiny robots have many promising applications in medical treatment including targeted drug delivery, non-invasive diagnosis, and minimally invasive surgery; and in micro-assembly/ -fabrication for Micro-Electro-Mechanical-Systems (MEMS). Microrobots are often deployed in large populations, and typically steered by uniform driving signals, including magnetic, electromagnetic, electrostatic, optical, gravitational, thermal, and chemical. The homogeneity of the microrobots and the uniformity of the control input make microrobot swarm manipulation difficult in constrained workspaces such as human vascular networks. The control laws and path-planning algorithms designed for macro-size robotics do not scale well to a microrobot swarm, so new methodology must be developed to address more efficient planning with constraints for a multi-agent problem in microscale. This thesis addresses the path-planning problem of a swarm of microrobots using a global control input. It begins with an introduction to state-of-the-art research and applications in microrobots. Chapter 2 gives an analysis of 2D and 3D position control of heterogeneous microrobots in the free space, together with demonstrations in simulations and hardware experiments. Motivated by the need for higher computational efficiency and capability of swarm manipulation with spatial constraints, chapter 3 discusses strategies of planning in 2D vascular networks for a swarm of homogeneous microrobots given a shared, global control input. Multiple path-planning methods and control algorithms are proposed, and their performance is compared in multiple vascular networks with different scale and complexity. The algorithms are validated with simulations and hardware experiments. Chapter 4 investigates reinforcement learning strategies to further improve path-planning efficiency, and to overcome local minima dilemmas in online algorithms. Chapter 5 reports automatic steering methods in multi-bifurcation vessels with flow, and reinforcement learning algorithms are implemented for improvement in microrobot delivery rate.