arXiv subjects

Jonathan Rogers

Publications and source records attributed to Jonathan Rogers.

9 recordsLinked to original sources

arXiv2026

PROPEL: A Memory-Driven, Adaptive Vector-Flow-Field Router with Process-Aware Waveguide Generation for Large-Scale Photonic Integrated Circuits

Photonic integrated circuits (PICs) are increasing in scale and routing complexity, driven by photonic computing, optical switching, programmable interferometer meshes, wavelength-routed optical networks-on-chip, and chip-to-chip optical interconnects. Manual waveguide planning becomes impractical as designs approach thousands of photonic components because routing must satisfy geometric, optical, electrical, and manufacturing constraints. This paper presents the Photonic Routing Optimization and Placement Engine (PROPEL), a memory-driven, native-accelerated adaptive vector-flow-field routing framework with process-aware waveguide generation for large-scale PIC design. PROPEL builds a routing kernel based on a bounded vector-flow-field algorithm and DRC validation. The same kernel supports passive optical routing, active optical-electrical routing, and topology-driven net assignment. C++ accelerates field and routing calculations, while Python performs detailed DRC replay, legality checking, route commitment, and GDSFactory-based geometry generation. Compared with state-of-the-art routing solutions, PROPEL is faster on 17 of 18 shared passive-routing cases, with a median speedup of 2.6x and a geometric-mean speedup of 2.5x, while maintaining zero design-rule violations. PROPEL also supports length, delay, and optical-path-length matching, process-map-aware waveguide generation, route-memory reuse, selective rip-up/reroute, and GDS-level legality replay. These capabilities address heterogeneous PIC layouts where optical, electrical, process, topology, matching, and manufacturability constraints must be handled together.

physics.optics↗

arXiv2026

Allocating Corrective Control to Mitigate Multi-agent Safety Violations Under Private Preferences

We propose a novel framework that computes the corrective control efforts to ensure joint safety in multi-agent dynamical systems. This framework efficiently distributes the required corrective effort without revealing individual agents' private preferences. Our framework integrates high-order control barrier functions (HOCBFs), which enforce safety constraints with formal guarantees of safety for complex dynamical systems, with a privacy-preserving resource allocation mechanism based on the progressive second price (PSP) auction. When a joint safety constraint is violated, agents iteratively bid on new corrective efforts via 'avoidance credits' rather than explicitly solving for feasible corrective efforts that remove the safety violation. The resulting correction, determined via a second price payment rule, coincides with the socially optimal safe distribution of corrective actions. Critically, the bidding process achieves this optimal allocation efficiently and without revealing private preferences of individual agents. We demonstrate this method through multi-robot hardware experiments on the Robotarium platform.

eess.SY↗

arXiv2025

When the Correct Model Fails: The Optimality of Stackelberg Equilibria with Follower Intention Updates

We study a two-player dynamic Stackelberg game where the follower's intention is unknown to the leader. Classical formulations of the Stackelberg equilibrium (SE) assume that the follower's best response (BR) function is known to the leader. However, this is not always true in practice. We study a setting in which the leader receives updated beliefs about the follower BR before the end of the game, such that the update prompts the leader and subsequently the follower to re-optimize their strategies. We characterize the optimality guarantees of the SE solutions under this belief update for both open loop and feedback information structures. Interestingly, we prove that in general, assuming an incorrect follower's BR may lead to a lower leader cost over the entire game than knowing the true follower's BR. We support these results with numerical examples in a linear quadratic (LQ) Stackelberg game, and use Monte Carlo simulations to show that the instances of incorrect BR achieving lower leader costs are non-trivial in collision avoidance LQ Stackelberg games.

eess.SY↗

arXiv2024

Arithmetical Structures on Coconut Trees

If G is a finite connected graph, then an arithmetical structure on $G$ is a pair of vectors $(\mathbf{d}, \mathbf{r})$ with positive integer entries such that $(\diag(\mathbf{d}) - A)\cdot \mathbf{r} = \mathbf{0}$, where $A$ is the adjacency matrix of $G$ and the entries of $\mathbf{r}$ have no common factor other than $1$. In this paper, we generalize the result of Archer, Bishop, Diaz-Lopez, Garc\'ia Puente, Glass, and Louwsma on enumerating arithmetical structures on bidents (also called coconut tree graphs $\CT{p}{2}$) to all coconut tree graphs $\CT{p}{s}$ which consists of a path on $p>0$ vertices to which we append $s>0$ leaves to the right most vertex on the path. We also give a characterization of smooth arithmetical structures on coconut trees when given number assignments to the leaf nodes.

math.CO↗

arXiv2020

The Koopman Expectation: An Operator Theoretic Method for Efficient Analysis and Optimization of Uncertain Hybrid Dynamical Systems

For dynamical systems involving decision making, the success of the system greatly depends on its ability to make good decisions with incomplete and uncertain information. By leveraging the Koopman operator and its adjoint property, we introduce the Koopman Expectation, an efficient method for computing expectations as propagated through a dynamical system. Unlike other Koopman operator-based approaches in the literature, this is possible without an explicit representation of the Koopman operator. Furthermore, the efficiencies enabled by the Koopman Expectation are leveraged for optimization under uncertainty when expected losses and constraints are considered. We show how the Koopman Expectation is applicable to discrete, continuous, and hybrid non-linear systems driven by process noise with non-Gaussian initial condition and parametric uncertainties. We finish by demonstrating a 1700x acceleration for calculating probabilistic quantities of a hybrid dynamical system over the naive Monte Carlo approach with many orders of magnitudes improvement in accuracy.

math.DS↗

arXiv2020

Cable Estimation-Based Control for Wire-Borne Underactuated Brachiating Robots: A Combined Direct-Indirect Adaptive Robust Approach

In this paper, we present an online adaptive robust control framework for underactuated brachiating robots traversing flexible cables. Since the dynamic model of a flexible body is unknown in practice, we propose an indirect adaptive estimation scheme to approximate the unknown dynamic effects of the flexible cable as an external force with parametric uncertainties. A boundary layer-based sliding mode control is then designed to compensate for the residual unmodeled dynamics and time-varying disturbances, in which the control gain is updated by an auxiliary direct adaptive control mechanism. Stability analysis and derivation of adaptation laws are carried out through a Lyapunov approach, which formally guarantees the stability and tracking performance of the robot-cable system. Simulation experiments and comparison with a baseline controller show that the combined direct-indirect adaptive robust control framework achieves reliable tracking performance and adaptive system identification, enabling the robot to traverse flexible cables in the presence of unmodeled dynamics, parametric uncertainties and unstructured disturbances.

cs.RO↗

arXiv2020

Robust Control Synthesis and Verification for Wire-Borne Underactuated Brachiating Robots Using Sum-of-Squares Optimization

Control of wire-borne underactuated brachiating robots requires a robust feedback control design that can deal with dynamic uncertainties, actuator constraints and unmeasurable states. In this paper, we develop a robust feedback control for brachiating on flexible cables, building on previous work on optimal trajectory generation and time-varying LQR controller design. We propose a novel simplified model for approximation of the flexible cable dynamics, which enables inclusion of parametric model uncertainties in the system. We then use semidefinite programming (SDP) and sum-of-squares (SOS) optimization to synthesize a time-varying feedback control with formal robustness guarantees to account for model uncertainties and unmeasurable states in the system. Through simulation, hardware experiments and comparison with a time-varying LQR controller, it is shown that the proposed robust controller results in relatively large robust backward reachable sets and is able to reliably track a pre-generated optimal trajectory and achieve the desired brachiating motion in the presence of parametric model uncertainties, actuator limits, and unobservable states.

cs.RO↗

arXiv2019

Feedback Control for Autonomous Riding of Hovershoes by a Cassie Bipedal Robot

Motivated towards achieving multi-modal locomotion, in this paper, we develop a framework for a bipedal robot to dynamically ride a pair of Hovershoes over various terrain. Our developed control strategy enables the Cassie bipedal robot to interact with the Hovershoes to balance, regulate forward and rotational velocities, achieve fast turns, and move over flat terrain, slopes, stairs, and rough outdoor terrain. Our sensor suite comprising of tracking and depth cameras for visual SLAM as well as our Dijkstra-based global planner and timed elastic band-based local planning framework enables us to achieve autonomous riding on the Hovershoes while navigating an obstacle course. We present numerical and experimental validations of our work.

cs.RO↗

arXiv2013

The effects of frequency-dependent quasar variability on the celestial reference frame

We examine the relationship between source position stability and astrophysical properties of radio-loud quasars making up the International Celestial Reference Frame. Understanding this relationship is important for improving quasar selection and analysis strategies, and therefore reference frame stability. We construct light curves for 95 of the most frequently observed ICRF2 quasars at both the 2.3 and 8.4 GHz geodetic VLBI observing bands. Because the appearance of new quasar components corresponds to an increase in quasar flux density, these light curves alert us to potential changes in source structure before they appear in VLBI images. We test how source position stability depends on three astrophysical parameters: (1) Flux density variability at X-band; (2) Time lag between flares in S and X-bands; (3) Spectral index rms, defined as the variability in the ratio between S and X-band flux densities. We find that small time lags between S and X-band light curves, and low spectral index variability, are good indicators of position stability. On the other hand, there is no strong dependence of source position stability on flux density variability in a single frequency band. These findings can be understood by interpreting the time lag between S and X-band light curves as a measure of the size of the source structure. Monitoring of source flux density at multiple frequencies therefore appears to provide a useful probe of quasar structure on scales important to geodesy. We show how multi-frequency flux density monitoring may allow the dependence on frequency of the relative core positions along the jet to be elucidated. Knowledge of the position-frequency relation has important implications for current and future geodetic VLBI programs, as well as the alignment between the radio and optical celestial reference frames. (Abridged)

astro-ph.CO↗