Aaron Becker

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The classical problem of robot coverage is to plan a path that brings a point on the robot within a fixed distance of every point in the free space. In the presence of significant uncertainty in sensing and actuation, it may no longer be possible to guarantee that the robot covers all of the free space all the time, and so it becomes unclear what problem we(More)
BACKGROUND Targeted agents such as tyrosine kinase inhibitors have been extensively studied in preclinical systems and in advanced-stage patients. Little is known about levels of kinase inhibitors found in tumors as opposed to plasma. Similarly, effects of inhibitors on tumor signaling pathways in patient-based materials are unclear. To explore these(More)
This paper considers the problem of steering a nonholonomic unicycle despite model perturbation that scales both the forward speed and the turning rate by an unknown but bounded constant. We model the unicycle as an ensemble control system, show that this system is ensemble controllable, and derive an approximate steering algorithm that brings the unicycle(More)
PURPOSE The quinazoline based alpha1-adrenoceptor antagonists doxazosin and terazosin suppress prostate tumor growth via the induction of apoptosis and decrease in tissue vascularity. To assess the effect of alpha1-blocker exposure on the incidence of prostate cancer we performed an exploratory, observational cohort study. MATERIALS AND METHODS The(More)
This paper presents a mechanism and a control strategy that enables automated non-contact manipulation of spherical objects in three dimensions using air flow, and demonstrates several tasks that can be performed with such a system. The mechanism is a 2-DOF gimbaled air jet with a variable flow rate. The control strategy is feedback linearization based on a(More)
This paper derives both open-loop and closed-loop control policies that steer a finite set of differential-drive robots to desired positions in a two-dimensional workspace, when all robots receive the same control inputs but each robot turns at a slightly different rate. In the absence of perturbation, the open-loop policy achieves zero error in finite(More)
We present fundamental progress on parallel self-assembly using large swarms of microscale particles in complex environments, controlled not by individual navigation, but by a uniform, global, external force with the same effect on each particle. Consider a 2-D grid world, in which all obstacles and particles are unit squares, and for each actuation,(More)
Roboticists, biologists, and chemists are now producing large populations of simple robots, but controlling large populations of robots with limited capabilities is difficult, due to communication and onboard-computation constraints. Direct human control of large populations seems even more challenging. In this paper we investigate control of mobile robots(More)
Micro- and nanorobotics have the potential to revolutionize many applications including targeted material delivery, assembly, and surgery. The same properties that promise breakthrough solutions - small size and large populations - present unique challenges to generating controlled motion. We want to use large swarms of robots to perform manipulation tasks;(More)
In this paper we investigate control of a large swarm of mobile particles (such as robots, sensors, or building material) that move in a 2D workspace using a global input signal, e.g., provided by gravity or a magnetic field. Upon activation, each robot moves in the same direction, maximally until it hits a stationary obstacle or another stationary robot.(More)