Abstract Background Autonomous underwater vehicles (AUVs) and animal telemetry have become important tools for understanding the relationships between aquatic organisms their environment, but more information is needed to guide development use of AUVs as effective tracking platforms. A forward-facing acoustic receiver (VR2Tx 69 kHz; VEMCO, Bedford, Nova Scotia) attached a novel AUV (gliding robotic fish) was tested in freshwater lake (1) compare its detection efficiency (i.e., probability...

Often times in nonlinear systems, the control input can play a significant role system's observability. In this paper, we investigate trade-off between observability and performance for mobile robot target tracking, when only distance to is measured. The problem motivated by practical applications autonomous robots operating GPS-denied environments. A model predictive (NMPC) framework used address dilemma localization jointly optimizing tracking an metric. Three measures of estimation are...

Automated vehicles' neural networks suffer from overfit, poor generalizability, and untrained edge cases due to limited data availability. Researchers synthesize randomized edge-case scenarios assist in the training process, though simulation introduces potential for overfit latent rules features. Automating worst-case scenario generation could yield informative improving self driving. To this end, we introduce a "Physically Adversarial Intelligent Network" (PAIN), wherein self-driving...

With the advent of 3D printing and increasing list available materials, various functional devices can be printed for low-cost, rapid prototyping. In particular, 3D-printed strain gauges show promise in multiple applications such as robotics structural health monitoring. However, characterization compensation thermal dependence have been limited literature. this work temperaturedependent resistive behavior is characterized with a commercially filament, conductive PLA (Polylactic Acid), which...

Abstract Autonomous underwater gliders have become valuable tools for a myriad of applications ranging from ocean exploration to fish tracking environmental sampling. To be suitable these types applications, precise sensing and monitoring is desired, which makes accurate trajectory control important. However, highly nonlinear under-actuated dynamics present significant challenges in gliders. In this work backstepping-based controller proposed an glider track desired position heading...

Autonomous underwater gliders have become valuable, energy-efficient tools for a myriad of applications including ocean exploration, fish tracking, and environmental sampling. Many applications, such as, exploring large area ruins or navigating through coral reef, would benefit from fine trajectory tracking. However, tracking control is particularly challenging due to their under-actuated, nonlinear dynamics. Taking gliding robotic as an example, in this work we propose backstepping-based...

Abstract In many nonlinear systems, the observability of system is dependent on its state and control input. Thus, incorporating into a scheme can enhance an observer's ability to recover accurate estimates unmeasured states, minimize estimation error, ultimately, allow original objective be achieved. The accommodation observability, however, may conflict with goal at times. this paper, we propose use barrier functions (CBFs) enforce thereby facilitate convergence estimate true while...

Abstract This paper presents an adaptive, needle variation-based feedback scheme for controlling affine nonlinear systems with unknown parameters that appear linearly in the dynamics. The proposed approach combines online parameter identifier a second-order sequential action controller has shown great promise nonlinear, underactuated, and high-dimensional constrained systems. Simulation results on dynamics of underwater glider robotic fish show advantages introducing estimation to when model...

Abstract In this paper, we derive a dynamical model for controllable flexible membrane which is point-actuated by distributed voice coil motors (VCM) connected to it. Besides the modal analysis of motion, only dynamics discussed in most related published works treating external pressures as inputs, integrate including mechanics and electrical into whole system, leaving signals inputs VCM-actuated useful practical application. Also, multiple-input-multiple-output (MIMO) system simplified...

Automated vehicles' neural networks suffer from overfit, poor generalizability, and untrained edge cases due to limited data availability. Researchers synthesize randomized edge-case scenarios assist in the training process, though simulation introduces potential for overfit latent rules features. Automating worst-case scenario generation could yield informative improving self driving. To this end, we introduce a "Physically Adversarial Intelligent Network" (PAIN), wherein self-driving...

In nonlinear systems, the control input often directly impacts observability of system. this paper, we investigate use barrier functions (CBFs) for enforcing a mobile robot in target tracking, when only distance to is measured. The problem motivated by practical applications autonomous robots operating GPS-denied environments. To address tradeoffs between localization accuracy and tracking performance, controller augmented function based on an metric. Two examples are used show efficacy...

Autonomous marine vehicles are deployed in oceans and lakes to collect spatio-temporal data. GPS is often used for localization, but inaccessible underwater. Poor localization underwater makes it difficult pinpoint where data collected, accurately map, or autonomously explore the ocean other aquatic environments. This paper proposes use of multifidelity Gaussian process regression incorporate associated with uncertain locations. With proposed approach, an adaptive sampling algorithm...

Intelligent physical systems as embodied cognitive must perform high-level reasoning while concurrently managing an underlying control architecture. The link between cognition and manage the problem of converting continuous values from real world to symbolic representations (and back). To generate effective behaviors, include a capacity replan, acquire update new information, detect respond anomalies, various operations on system goals. But, these processes are not independent need further...