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Integrating Contact-aware Feedback CPG System for Learning-based Soft Snake Robot Locomotion Controllers

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arXiv 2023年

作者： Liu, Xuan Onal, Cagdas D. Fu, Jie The Robotics Engineering Department Worcester Polytechnic Institute WorcesterMA United States The Department of Electrical and Computer Engineering University of Florida GainesvilleFL United States

This paper aims to solve the contact-aware locomotion problem of a soft snake robot by developing bio-inspired contact-aware locomotion controllers. To provide effective contact information for the controllers, we develop a scale-covered sensor structure mimicking natural snakes' scale sensilla. In the design of the control framework, our core contribution is the development of a novel sensory feedback mechanism for the Matsuoka central pattern generator (CPG) network. This mechanism allows the Matsuoka CPG system to work like a "spinal cord" in the whole contact-aware control scheme, which simultaneously takes the stimuli including tonic input signals from the "brain" (a goal-tracking locomotion controller) and sensory feedback signals from the "reflex arc" (the contact reactive controller), and generates rhythmic signals to actuate the soft snake robot to slither through densely allocated obstacles. In the "reflex arc" design, we develop two distinctive types of reactive controllers - 1) a reinforcement learning (RL) sensor regulator that learns to manipulate the sensory feedback inputs of the CPG system, and 2) a local reflexive sensor-CPG network that directly connects sensor readings and the CPG's feedback inputs in a specific topology. Combining with the locomotion controller and the Matsuoka CPG system, these two reactive controllers facilitate two different contact-aware locomotion control schemes. The two control schemes are tested and evaluated in both simulated and real soft snake robots, showing promising performance in the contact-aware locomotion tasks. The experimental results also validate the advantages of the modified Matsuoka CPG system with a new sensory feedback mechanism for bio-inspired robot controller design. © 2023, CC BY.

关键词： Controllers

Towards Accurate Loop Closure Detection in Semantic SLAM with 3D Semantic Covisibility Graphs

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arXiv 2023年

作者： Qian, Zhentian Fu, Jie Xiao, Jing The Robotics Engineering Department Worcester Polytechnic Institute WorcesterMA United States The Department of Electrical and Computer Engineering University of Florida GainesvilleFL United States

Loop closure is necessary for correcting errors accumulated in simultaneous localization and mapping (SLAM) in unknown environments. However, conventional loop closure methods based on low-level geometric or image features may cause high ambiguity by not distinguishing similar scenarios. Thus, incorrect loop closures can occur. Though semantic 2D image information is considered in some literature to detect loop closures, there is little work that compares 3D scenes as an integral part of a semantic SLAM system. This paper introduces an approach, called SmSLAM+LCD, integrated into a semantic SLAM system to combine high-level 3D semantic information and low-level feature information to conduct accurate loop closure detection and effective drift reduction. The effectiveness of our approach is demonstrated in testing results. © 2023, CC BY.

关键词： Semantics

Pilot-wave dynamics: Using dynamic mode decomposition to characterize bifurcations, routes to chaos, and emergent statistics

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Physical Review E 2023年第3期108卷 034213-034213页

作者： J. Nathan Kutz André Nachbin Peter J. Baddoo John W. M. Bush Department of Applied Mathematics and Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA Department of Mathematical Sciences Worcester Polytechnic Institute Worcester Massachusetts 01742 USA Department of Mathematics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA

We develop a data-driven characterization of the pilot-wave hydrodynamic system in which a bouncing droplet self-propels along the surface of a vibrating bath. We consider drop motion in a confined one-dimensional geometry and apply the dynamic mode decomposition (DMD) in order to characterize the evolution of the wave field as the bath's vibrational acceleration is increased progressively. Dynamic mode decomposition provides a regression framework for adaptively learning a best-fit linear dynamics model over snapshots of spatiotemporal data. Thus, DMD reduces the complex nonlinear interactions between pilot waves and droplet to a low-dimensional linear superposition of DMD modes characterizing the wave field. In particular, it provides a low-dimensional characterization of the bifurcation structure of the pilot-wave physics, wherein the excitation and recruitment of additional modes in the linear superposition models the bifurcation sequence. This DMD characterization yields a fresh perspective on the bouncing-droplet problem that forges valuable new links with the mathematical machinery of quantum mechanics. Specifically, the analysis shows that as the vibrational acceleration is increased, the pilot-wave field undergoes a series of Hopf bifurcations that ultimately lead to a chaotic wave field. The established relation between the mean pilot-wave field and the droplet statistics allows us to characterize the evolution of the emergent statistics with increased vibrational forcing from the evolution of the pilot-wave field. We thus develop a numerical framework with the same basic structure as quantum mechanics, specifically a wave theory that predicts particle statistics.

关键词： Dynamical systems

Exploring Anatomical Similarity in Cardiac-Gated Spect Images for A Deep Learning Network 30

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Exploring Anatomical Similarity in Cardiac-Gated Spect Image...

30th IEEE International Conference on Image Processing, ICIP 2023

作者： Zhang, Xirang Yang, Yongyi Pretorius, P. Hendrik King, Michael A. Illinois Institute of Technology Department of Electrical and Computer Engineering ChicagoIL60616 United States University of Massachusetts Medical School Department of Radiology WorcesterMA01655 United States

ISBN: (纸本)9781728198354

Motion compensation is effective for reducing motion blur in cardiac gated imaging. In this work, we investigate the potential benefit of incorporating an anatomical similarity measure in training a deep learning (DL) network for motion compensation on cardiac gated SPECT images, which are known to suffer from limited data counts and exhibit image intensity distortion (due to partial-volume effect) associated with cardiac motion. In this similarity measure we utilize the spatial image gradient to characterize the correspondence of boundary points on the left-ventricular wall between two gate frames. In the experiment we demonstrated this approach on a set of 197 clinical acquisitions, and the results show that with the proposed approach the DL network can improve the anatomical similarity among the gate frames upon motion compensation. © 2023 IEEE.

关键词： Motion compensation

Latency Analysis of Vehicle-to-Pedestrian C-V2X Communications at Urban Street Intersections

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arXiv 2022年

作者： Gill, Kuldeep S. Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA United States

Cellular Vehicle-to-Everything (C-V2X) technology promises to provide ultra-reliable low latency communication (URLLC) framework for connected vehicles. Connected vehicles can help us improve traffic safety, congestion and reduce fatal accidents. C-V2X promises new levels of connectivity and intelligence providing numerous features like infotainment, always-on telematics, real-time navigation, etc. with heterogeneous network architecture. C-V2X leverages existing cellular architecture and is on the way to replace DSRC/WAVE for vehicular communication. There are still some challenges which needs to be tackled before C-V2X can be deployed for efficient on-road V2X. In this paper, we look at end-to-end latency for Vehicle-to-Pedestrian (V2P) which demands ultra low latencies with reliable packet delivery ratio. To evaluate the LTE-V2P performance, we used network simulator for an urban intersection scenario where vulnerable road-side users (VRUs) are trying to cross the street and they communicate with moving vehicles. We evaluated the end-to-end latency and throughput for the given scenario and concluded that with the existing network architecture the latency is high. By utilizing multi-edge access computing (MEC) servers latency can be reduce drastically and hence can be made feasible for cellular V2P communication. © 2022, CC BY-SA.

关键词： Vehicle to Everything

A Survey on Visual Map Localization Using LiDARs and Cameras

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arXiv 2022年

作者： Elhousni, Mahdi Huang, Xinming Electrical and Computer Engineering department Worcester Polytechnic Institute WorcesterMA United States

As the autonomous driving industry is slowly maturing, visual map localization is quickly becoming the standard approach to localize cars as accurately as possible. Owing to the rich data returned by visual sensors such as cameras or LiDARs, researchers are able to build different types of maps with various levels of details, and use them to achieve high levels of vehicle localization accuracy and stability in urban environments. Contrary to the popular SLAM approaches, visual map localization relies on pre-built maps, and is focused solely on improving the localization accuracy by avoiding error accumulation or drift. We define visual map localization as a two-stage process. At the stage of place recognition, the initial position of the vehicle in the map is determined by comparing the visual sensor output with a set of geo-tagged map regions of interest. Subsequently, at the stage of map metric localization, the vehicle is tracked while it moves across the map by continuously aligning the visual sensors’ output with the current area of the map that is being traversed. In this paper, we survey, discuss and compare the latest methods for LiDAR based, camera based and cross-modal visual map localization for both stages, in an effort to highlight the strength and weakness of each approach. Copyright © 2022, The Authors. All rights reserved.

关键词： Cameras

PAAMP: Polytopic Action-Set And Motion Planning for Long Horizon Dynamic Motion Planning via Mixed Integer Linear Programming

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arXiv 2024年

作者： Jaitly, Akshay Farzan, Siavash Robotics Engineering Department Worcester Polytechnic Institute WorcesterMA01609 United States Electrical Engineering Department California Polytechnic State University San Luis ObispoCA93407 United States

— Optimization methods for long-horizon, dynamically feasible motion planning in robotics tackle challenging non-convex and discontinuous optimization problems. Traditional methods often falter due to the nonlinear characteristics of these problems. We introduce a technique that utilizes learned representations of the system, known as Polytopic Action Sets, to efficiently compute long-horizon trajectories. By employing a suitable sequence of Polytopic Action Sets, we transform the long-horizon dynamically feasible motion planning problem into a Linear Program. This reformulation enables us to address motion planning as a Mixed Integer Linear Program (MILP). We demonstrate the effectiveness of a Polytopic Action-Set and Motion Planning (PAAMP) approach by identifying swing-up motions for a torque-constrained pendulum as fast as 0.75 milliseconds. This approach is well-suited for solving complex motion planning and long-horizon Constraint Satisfaction Problems (CSPs) in dynamic and underactuated systems such as legged and aerial robots. Copyright © 2024, The Authors. All rights reserved.

关键词： Mixed-integer linear programming

Performance Analysis of a Flexible HPTS-Based Carbon Dioxide Sensor for Transcutaneous Blood Gas Monitoring

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Performance Analysis of a Flexible HPTS-Based Carbon Dioxide...

IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Tuna B. Tufan Kleo Golemi Evan Apinis Kosti Pano Zach Hetzler Qingshan Wei Ulkuhan Guler Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA Department of Chemical and Biomolecular Engineering North Carolina State University Raleigh NC USA

Traditional transcutaneous carbon dioxide sensing methods often require frequent calibration and the replacement of measurement electrodes, often deployed in large devices. In our pursuit of developing an accurate and noninvasive method for transcutaneous carbon dioxide sensing, we have introduced the utilization of a carbon dioxide-sensitive flexible sensor patch consisted of 8-hydroxypyrene-1,3,6-trisulfonate. To assess its performance, we have designed custom circuitry and conducted various tests to evaluate the sensor’s reactivity to changes in the partial pressure of carbon dioxide, as well as its response to external parameters, such as excitation intensity, measurement drift, humidity, and temperature. Through our testing, we implemented a ratiometric approach and discovered that the sensor exhibits a linear relationship between the luminescence ratio and changes in carbon dioxide partial pressure. Within the clinically relevant range, we successfully measured carbon dioxide partial pressure, showing a variation of less than 3.9% across different levels of excitation intensity.

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Learning-Based Design of Off-Policy Gaussian Controllers: Integrating Model Predictive Control and Gaussian Process Regression

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arXiv 2024年

作者： Tekumatla, Shiva Kumar Gampa, Varun Farzan, Siavash The Robotics Engineering Department Worcester Polytechnic Institute WorcesterMA01609 United States The Electrical Engineering Department California Polytechnic State University San Luis ObispoCA93407 United States

This paper presents an off-policy Gaussian Predictive Control (GPC) framework aimed at solving optimal control problems with a smaller computational footprint, thereby facilitating real-time applicability while ensuring critical safety considerations. The proposed controller imitates classical control methodologies by modeling the optimization process through a Gaussian process and employs Gaussian Process Regression to learn from the Model Predictive Control (MPC) algorithm. Notably, the Gaussian Process setup does not incorporate a built-in model, enhancing its applicability to a broad range of control problems. We applied this framework experimentally to a differential drive mobile robot, tasking it with trajectory tracking and obstacle avoidance. Leveraging the off-policy aspect, the controller demonstrated adaptability to diverse trajectories and obstacle behaviors. Simulation experiments confirmed the effectiveness of the proposed GPC method, emphasizing its ability to learn the dynamics of optimal control strategies. Consequently, our findings highlight the significant potential of off-policy Gaussian Predictive Control in achieving real-time optimal control for handling of robotic systems in safety-critical scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control