Vision-based neural formation tracking control of multiple autonomous vehicles with visibility and performance constraints

2021 ◽  
Author(s):  
Shude He ◽  
Rourou Xu ◽  
Zhijia Zhao ◽  
Tao Zou
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Performance Constraints ◽  
Formation Tracking ◽  
And Performance

scholarly journals Trajectory Tracking Control of Parallel Manipulator Based on Udwadia-Kalaba Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Chenming Li ◽  
Han Zhao ◽  
Shengchao Zhen ◽  
Kang Huang ◽  
Hao Sun ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Parallel Manipulator ◽  
Structural Constraints ◽  
Constraint Forces ◽  
Trajectory Tracking Control ◽  
Lagrangian Multipliers ◽  
Explicit Equation ◽  
Performance Constraints ◽  
And Performance

There have been many approaches for achieving the trajectory tracking control of parallel manipulator. However, these approaches are complex for calculating Lagrangian multipliers. In this paper, unlike the former approaches, a new approach of trajectory tracking control which is based on Udwadia-Kalaba approach is presented. Using this methodology, we can obtain a concise and explicit equation of motion and consider holonomic and nonholonomic constraint whether it is ideal or nonideal simultaneously. The most important difference is that we divide constraints into structural constraints and performance constraints in this paper. Structural constraints are used to establish dynamic model without regard for trajectory control. And performance constraints are used to represent the desired trajectory. For the parallel manipulator, a nonlinear dynamics system, its constraint forces are obtained by second-order constraints. And the numerical simulation in MATLAB shows the parallel manipulator’s movement meets the requirement; tracking trajectory is exact and perfect. Through this paper, we can see that the method can simplify calculation availably.

Decentralized formation-tracking control of autonomous vehicles on straight paths

2014 ◽  
Author(s):  
Antonio Loria ◽  
Janset Dasdemir ◽  
Nohemi Jarquin-Alvarez
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Formation Tracking

scholarly journals Formation-Tracking Control of Autonomous Vehicles Under Relaxed Persistency of Excitation Conditions

2018 ◽  
Vol 26 (5) ◽  
pp. 1860-1865 ◽  
Author(s):  
Mohamed Maghenem ◽  
Antonio Loria ◽  
Elena Panteley
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Formation Tracking ◽  
Persistency Of Excitation ◽  
Excitation Conditions

scholarly journals A 4-DOF Upper Limb Exoskeleton for Physical Assistance: Design, Modeling, Control and Performance Evaluation

2021 ◽  
Vol 11 (13) ◽  
pp. 5865
Author(s):  
Muhammad Ahsan Gull ◽  
Mikkel Thoegersen ◽  
Stefan Hein Bengtson ◽  
Mostafa Mohammadi ◽  
Lotte N. S. Andreasen Struijk ◽  
...  
Keyword(s):  
Upper Limb ◽  
Tracking Control ◽  
Degrees Of Freedom ◽  
Control Method ◽  
Mechanical Design ◽  
Trajectory Tracking Control ◽  
Upper Limb Exoskeleton ◽  
And Performance ◽  
Physically Disabled People ◽  
Human Upper Limb

Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.

Spherical Formation Tracking Control of Nonlinear Second-Order Agents With Adaptive Neural Flow Estimate

2021 ◽  
pp. 1-12
Author(s):  
Yang-Yang Chen ◽  
Rong Huang ◽  
Yanteng Ge ◽  
Ya Zhang
Keyword(s):  
Tracking Control ◽  
Second Order ◽  
Formation Tracking

scholarly journals Road Characteristics Detection Based on Joint Convolutional Neural Networks with Adaptive Squares

2021 ◽  
Vol 10 (6) ◽  
pp. 377
Author(s):  
Chiao-Ling Kuo ◽  
Ming-Hua Tsai
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Autonomous Vehicles ◽  
Detection Accuracy ◽  
Geospatial Information ◽  
Combination Rules ◽  
And Performance ◽  
Road Characteristics ◽  
Machine Readable ◽  
Background Image

The importance of road characteristics has been highlighted, as road characteristics are fundamental structures established to support many transportation-relevant services. However, there is still huge room for improvement in terms of types and performance of road characteristics detection. With the advantage of geographically tiled maps with high update rates, remarkable accessibility, and increasing availability, this paper proposes a novel simple deep-learning-based approach, namely joint convolutional neural networks (CNNs) adopting adaptive squares with combination rules to detect road characteristics from roadmap tiles. The proposed joint CNNs are responsible for the foreground and background image classification and various types of road characteristics classification from previous foreground images, raising detection accuracy. The adaptive squares with combination rules help efficiently focus road characteristics, augmenting the ability to detect them and provide optimal detection results. Five types of road characteristics—crossroads, T-junctions, Y-junctions, corners, and curves—are exploited, and experimental results demonstrate successful outcomes with outstanding performance in reality. The information of exploited road characteristics with location and type is, thus, converted from human-readable to machine-readable, the results will benefit many applications like feature point reminders, road condition reports, or alert detection for users, drivers, and even autonomous vehicles. We believe this approach will also enable a new path for object detection and geospatial information extraction from valuable map tiles.

scholarly journals Formation Tracking Control and Obstacle Avoidance of Unicycle-Type Robots Guaranteeing Continuous Velocities

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4374
Author(s):  
Jose Bernardo Martinez ◽  
Hector M. Becerra ◽  
David Gomez-Gutierrez
Keyword(s):  
Obstacle Avoidance ◽  
Tracking Control ◽  
Global Coordinate System ◽  
Avoidance Task ◽  
Time Varying ◽  
Control Laws ◽  
Formation Tracking ◽  
Control Scheme ◽  
First Time ◽  
Hierarchical Scheme

In this paper, we addressed the problem of controlling the position of a group of unicycle-type robots to follow in formation a time-varying reference avoiding obstacles when needed. We propose a kinematic control scheme that, unlike existing methods, is able to simultaneously solve the both tasks involved in the problem, effectively combining control laws devoted to achieve formation tracking and obstacle avoidance. The main contributions of the paper are twofold: first, the advantages of the proposed approach are not all integrated in existing schemes, ours is fully distributed since the formulation is based on consensus including the leader as part of the formation, scalable for a large number of robots, generic to define a desired formation, and it does not require a global coordinate system or a map of the environment. Second, to the authors’ knowledge, it is the first time that a distributed formation tracking control is combined with obstacle avoidance to solve both tasks simultaneously using a hierarchical scheme, thus guaranteeing continuous robots velocities in spite of activation/deactivation of the obstacle avoidance task, and stability is proven even in the transition of tasks. The effectiveness of the approach is shown through simulations and experiments with real robots.

Passthrough+

2020 ◽  
Vol 3 (1) ◽  
pp. 1-17
Author(s):  
Gaurav Chaurasia ◽  
Arthur Nieuwoudt ◽  
Alexandru-Eugen Ichim ◽  
Richard Szeliski ◽  
Alexander Sorkine-Hornung
Keyword(s):  
Real Time ◽  
Video Encoding ◽  
View Synthesis ◽  
Performance Constraints ◽  
Trade Offs ◽  
Stereoscopic View ◽  
Target User ◽  
Spatio Temporal ◽  
And Performance ◽  
3D Scene

We present an end-to-end system for real-time environment capture, 3D reconstruction, and stereoscopic view synthesis on a mobile VR headset. Our solution allows the user to use the cameras on their VR headset as their eyes to see and interact with the real world while still wearing their headset, a feature often referred to as Passthrough. The central challenge when building such a system is the choice and implementation of algorithms under the strict compute, power, and performance constraints imposed by the target user experience and mobile platform. A key contribution of this paper is a complete description of a corresponding system that performs temporally stable passthrough rendering at 72 Hz with only 200 mW power consumption on a mobile Snapdragon 835 platform. Our algorithmic contributions for enabling this performance include the computation of a coarse 3D scene proxy on the embedded video encoding hardware, followed by a depth densification and filtering step, and finally stereoscopic texturing and spatio-temporal up-sampling. We provide a detailed discussion and evaluation of the challenges we encountered, as well as algorithm and performance trade-offs in terms of compute and resulting passthrough quality.;AB@The described system is available to users as the Passthrough+ feature on Oculus Quest. We believe that by publishing the underlying system and methods, we provide valuable insights to the community on how to design and implement real-time environment sensing and rendering on heavily resource constrained hardware.

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