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  1. Free, publicly-accessible full text available June 1, 2023
  2. This paper presents four data-driven system models for a magnetically controlled swimmer. The models were derived directly from experimental data, and the accuracy of the models was experimentally demonstrated. Our previous study successfully implemented two non-model-based control algorithms for 3D path-following using PID and model reference adaptive controller (MRAC). This paper focuses on system identification using only experimental data and a model-based control strategy. Four system models were derived: (1) a physical estimation model, (2, 3) Sparse Identification of Nonlinear Dynamics (SINDY), linear system and nonlinear system, and (4) multilayer perceptron (MLP). All four system models were implemented as an estimator of a multi-step Kalman filter. The maximum required sensing interval was increased from 180 ms to 420 ms and the respective tracking error decreased from 9 mm to 4.6 mm. Finally, a Model Predictive Controller (MPC) implementing the linear SINDY model was tested for 3D path-following and shown to be computationally efficient and offers performances comparable to other control methods.
    Free, publicly-accessible full text available May 23, 2023
  3. Free, publicly-accessible full text available April 1, 2023
  4. This paper investigates the pursuit-evasion problem of a defensive gun turret and one or more attacking drones. The turret must "visit" each attacking drone once, as quickly as possible, to defeat the threat. This constitutes a Shortest Hamiltonian Path (SHP) through the drones. The investigation considers situations with increasing fidelity, starting with a 2D kinematic model and progressing to a 3D dynamic model. In 2D we determine the region from which one or more drones can always reach a turret, or the region close enough to it where they can evade the turret. This provides optimal starting angles for n drones around a turret and the maximum starting radius for one and two drones.We show that safety regions also exist in 3D and provide a controller so that a drone in this region can evade the pan-tilt turret. Through simulations we explore the maximum range n drones can start and still have at least one reach the turret, and analyze the effect of turret behavior and the drones’ number, starting configuration, and behaviors.
  5. Quadcopters are increasingly popular for robotics applications. Being able to efficiently calculate the set of positions reachable by a quadcopter within a time budget enables collision avoidance and pursuit-evasion strategies.This paper examines the set of positions reachable by a quadcopter within a specified time limit using a simplified 2D model for quadcopter dynamics. This popular model is used to determine the set of candidate optimal control sequences to build the full 3D reachable set. We calculate the analytic equations that exactly bound the set of positions reachable in a given time horizon for all initial conditions. To further increase calculation speed, we use these equations to derive tight upper and lower spherical bounds on the reachable set.
  6. We consider a robot tasked with observing its environment and later selectively summarizing what it saw as a vivid, structured narrative. The robot interacts with an uncertain environment, modelled as a stochastic process, and must decide what events to pay attention to (substance), and how to best make its recording (style) for later compilation of its summary. If carrying a video camera, for example, it must decide where to be, what to aim the camera at, and which stylistic selections, like the focus and level of zoom, are most suitable. This paper examines planning algorithms that help the robot predict events that (1) will likely occur; (2) would be useful in telling a tale; and (3) may be hewed to cohere stylistically. The third factor, a time-extended requirement, is entirely neglected in earlier, simpler work. With formulations based on underlying Markov Decision Processes, we compare two algorithms: a monolithic planner that jointly plans over events and style pairs and a decoupled approach that prescribes style conditioned on events. The decoupled approach is seen to be effective and much faster to compute, suggesting that computational expediency justifies the separation of substance from style. Finally, we also report on our hardware implementation.
  7. Soil strength testing and collecting soil cores from wetlands is currently a slow, manual process that runs the risk of disturbing and contaminating soil samples. This paper describes a method using an instrumented dart deployed and retrieved by a drone for performing core sample tests in soft soils. The instrumented dart can simultaneously conduct free- fall penetrometer tests. A drone-mounted mechanism enables deploying and reeling in the dart for sample return or for multiple soil strength tests. Tests examine the effect of dart tip diameter and drop height on soil retrieval, and the requisite pull force to retrieve the samples. Further tests examine the dart’s ability to measure soil strength and penetration depth. Hardware trials demonstrate that the drone can repeatedly drop and retrieve a dart, and that the soil can be discretely sampled.
  8. This paper presents a method for performing free-fall penetrometer tests for soft soils using an instrumented dart deployed by a quadcopter. Tests were performed with three soil types and used to examine the effect of drop height on the penetration depth and the deceleration profile. Further tests analyzed the force required to remove a dart from the soil and the effect of pulling at different speeds and angles. The pull force of a consumer drone was measured, and tests were performed where a drone delivered and removed darts in soil representative of a wetland environment.
  9. Localization is a key ability for robot navigation and collision avoidance. The advent of technologies such as GPS have led to many improvements in terrestrial navigation. Unfortunately traditional electromagnetic (EM) communications propagate poorly through lossy media such as underwater and underground. Therefore, localization remains a challenging problem in such environments, necessitating other approaches such as acoustics and magnetic induction (MI). This paper investigates estimating the relative location of a pair of MI triaxial coil antennas in air, as a preliminary step to underwater applications. By measuring the voltages induced in the receiving antenna when the transmitting antenna's coils are turned on sequentially, the distance between the antennas can be computed. Then, with knowledge of the current velocities of the antennas, we can apply a particle filter to generate an estimate of the location of the transmitting antenna with respect to the receiving one. The theory is supported by simulations and later verified through a series of experiments.