Distributed Receding Horizon Control with Application to Multi-Vehicle Formation Stabilization

We consider the control of interacting subsystems whose dynamics and constraints are uncoupled, but whose state vectors are coupled non-separably in a single centralized cost function of a finite horizon optimal control problem. For a given centralized cost structure, we generate distributed optimal control problems for each subsystem and establish that the distributed receding horizon implementation is asymptotically stabilizing. The communication requirements between subsystems with coupling in the cost function are that each subsystem obtain the previous optimal control trajectory of those subsystems at each receding horizon update. The key requirements for stability are that each distributed optimal control not deviate too far from the previous optimal control, and that the receding horizon updates happen sufficiently fast. The theory is applied in simulation for stabilization of a formation of vehicles

Model-based estimation of off-highway road geometry using single-axis LADAR and inertial sensing

This paper applies some previously studied extended Kalman filter techniques for planar road geometry estimation to the domain of autonomous navigation of off-highway vehicles. In this work, a clothoid model of the road geometry is constructed and estimated recursively based on road features extracted from single-axis LADAR range measurements. We present a method for feature extraction of the road centerline in the image plane, and describe its application to recursive estimation of the road geometry. We analyze the performance of our method against simulated motion of varied road geometries and against closed-loop detection, tracking and following of desert roads. Our method accomodates full 6 DOF motion of the vehicle as it navigates, constructs consistent estimates of the road geometry with respect to a fixed global reference frame, and requires an estimate of the sensor pose for each range measurement

Safety Verification of Fault Tolerant Goal-based Control Programs with Estimation Uncertainty

Fault tolerance and safety verification of control systems that have state variable estimation uncertainty are essential for the success of autonomous robotic systems. A software control architecture called mission data system, developed at the Jet Propulsion Laboratory, uses goal networks as the control program for autonomous systems. Certain types of goal networks can be converted into linear hybrid systems and verified for safety using existing symbolic model checking software. A process for calculating the probability of failure of certain classes of verifiable goal networks due to state estimation uncertainty is presented. A verifiable example task is presented and the failure probability of the control program based on estimation uncertainty is found

Safety verification of a fault tolerant reconfigurable autonomous goal-based robotic control system

Fault tolerance and safety verification of control systems are essential for the success of autonomous robotic systems. A control architecture called Mission Data System (MDS), developed at the Jet Propulsion Laboratory, takes a goal-based control approach. In this paper, a method for converting goal network control programs into linear hybrid systems is developed. The linear hybrid system can then be verified for safety in the presence of failures using existing symbolic model checkers. An example task is simulated in MDS and successfully verified using HyTech, a symbolic model checking software for linear hybrid systems

A new approach to teaching feedback

The Control and Dynamical Systems (CDS) Department at the California Institute of Technology (Caltech) has revised its entry-level curriculum in dynamics, feedback, and control with the goals of updating the subject matter to include modern tools and making control tools accessible to a nontraditional audience. One of the approaches made was to divide the introductory control theory class into two tracks, with a conceptual track geared toward students who need only a conceptual overview of control tools and an analytical track providing a more detailed mathematical treatment of feedback. The conceptual track, CDS 101, which is mainly discussed in the paper, is intended for advanced students in science and engineering who can benefit from an overview of control techniques but who might not have the need for the mathematical depth underlying the material. Special attention is paid to ensuring that the course is accessible to students from biological, physical, and information sciences, using examples from these domains to illustrate concepts. The goal of the course is to enable students to use the principles and tools of feedback in their research activities

Patching task-level robot controllers based on a local µ-calculus formula

We present a method for mending strategies for GR(1) specifications. Given the addition or removal of edges from the game graph describing a problem (essentially transition rules in a GR(1) specification), we apply a µ-calculus formula to a neighborhood of states to obtain a “local strategy” that navigates around the invalidated parts of an original synthesized strategy. Our method may thus avoid global resynthesis while recovering correctness with respect to the new specification. We illustrate the results both in simulation and on physical hardware for a planar robot surveillance task

A sufficient pipeline of doctors for rural communities is vital for Australia's overall medical workforce

The shortage of doctors in remote, rural and regional Australian communities is a longstanding health policy challenge. It is the main reason why almost 3000 overseas-trained doctors enter the labour force annually1 — a similar number to the domestic graduate output of Australian medical schools.2 Most overseas-trained doctors end up practising in major cities; 75% of all registered overseas-trained doctors in clinical practice in 2021 were metropolitan based, with major cities also accounting for 76% of the growth in overseas-trained doctors over the 2015–2021 period.3 In effect, rurally targeted recruitment of overseas-trained doctors compounds the problem of geographic maldistribution that it is meant to solve. Achieving a substantial pipeline of Australian-trained graduates who will willingly pursue regional careers as general practitioners, rural generalists and non-GP specialists is therefore a first order policy priority

Centennial- to millennial-scale hard rock erosion rates deduced from luminescence-depth profiles

The measurement of erosion and weathering rates in different geomorphic settings and over diverse temporal and spatial scales is fundamental to the quantification of rates and patterns of earth surface processes. A knowledge of the rates of these surface processes helps one to decipher their relative contribution to landscape evolution – information that is crucial to understanding the interaction between climate, tectonics and landscape. Consequently, a wide range of techniques has been developed to determine short- (<102 a) and long-term (>104 a) erosion rates. However, no method is available to quantify hard rock erosion rates at centennial to millennial timescales. Here we propose a novel technique, based on the solar bleaching of luminescence signals with depth into rock surfaces, to bridge this analytical gap. We apply our technique to glacial and landslide boulders in the Eastern Pamirs, China. The calculated erosion rates from the smooth varnished surfaces of 7 out of the 8 boulders sampled in this study vary between <0.038±0.002 and 1.72±0.04 mmka-1 (the eighth boulder gave an anomalously high erosion rate, possibly due to a recent chipping/cracking loss of surface). Given this preferential sampling of smooth surfaces, assumed to arise from grain-by-grain surface loss, we consider these rates as minimum estimates of rock surface denudation rates in the Eastern Pamirs, China

Regulatory activity revealed by dynamic correlations in gene expression noise

Gene regulatory interactions are context dependent, active in some cellular states but not in others. Stochastic fluctuations, or 'noise', in gene expression propagate through active, but not inactive, regulatory links^(1,2). Thus, correlations in gene expression noise could provide a noninvasive means to probe the activity states of regulatory links. However, global, 'extrinsic', noise sources generate correlations even without direct regulatory links. Here we show that single-cell time-lapse microscopy, by revealing time lags due to regulation, can discriminate between active regulatory connections and extrinsic noise. We demonstrate this principle mathematically, using stochastic modeling, and experimentally, using simple synthetic gene circuits. We then use this approach to analyze dynamic noise correlations in the galactose metabolism genes of Escherichia coli. We find that the CRP-GalS-GalE feed-forward loop is inactive in standard conditions but can become active in a GalR mutant. These results show how noise can help analyze the context dependence of regulatory interactions in endogenous gene circuits

Biologically Inspired Feedback Design for Drosophila Flight

We use a biologically motivated model of the Drosophila's flight mechanics and sensor processing to design a feedback control scheme to regulate forward flight. The model used for insect flight is the grand unified fly (GUF) [3] simulation consisting of rigid body kinematics, aerodynamic forces and moments, sensory systems, and a 3D environment model. We seek to design a control algorithm that will convert the sensory signals into proper wing beat commands to regulate forward flight. Modulating the wing beat frequency and mean stroke angle produces changes in the flight envelope. The sensory signals consist of estimates of rotational velocity from the haltere organs and translational velocity estimates from visual elementary motion detectors (EMD's) and matched retinal velocity filters. The controller is designed based on a longitudinal model of the flight dynamics. Feedforward commands are generated based on a desired forward velocity. The dynamics are linearized around this operating point and a feedback controller designed to correct deviations from the operating point. The control algorithm is implemented in the GUF simulator and achieves the desired tracking of the forward reference velocities and exhibits biologically realistic responses