A Study on RFID-based Arbitrary Point-to-Point Navigation and Path Recovery System for Mobile Robots

2021 ◽  
Author(s):  
Osaki Nakamatsu ◽  
Tomotaka Wada
Keyword(s):  
Mobile Robots ◽  
Arbitrary Point ◽  
Recovery System ◽  
Point To Point

Reducing Trajectory Tracking Error of Flexible Mobile Robots Using Command Shaping With Error-Limiting Constraints

2017 ◽  
Author(s):  
Gerald Eaglin ◽  
Joshua Vaughan
Keyword(s):  
Mobile Robots ◽  
Trajectory Tracking ◽  
Tracking Error ◽  
Input Shaping ◽  
Flexible Systems ◽  
Command Shaping ◽  
Modeling Errors ◽  
Temporal Tracking ◽  
Point Motion ◽  
Point To Point

The ability to track a trajectory without significant error is a vital requirement for mobile robots. Numerous methods have been proposed to mitigate tracking error. While these trajectory-tracking methods are efficient for rigid systems, many excite unwanted vibration when applied to flexible systems, leading to tracking error. This paper analyzes a modification of input shaping, which has been primarily used to limit residual vibration for point-to-point motion of flexible systems. Standard input shaping is modified using error-limiting constraints to reduce transient tracking error for the duration of the system’s motion. This method is simulated with trajectory inputs constructed using line segments and Catmull-Rom splines. Error-limiting commands are shown to improve both spatial and temporal tracking performance and can be made robust to modeling errors in natural frequency.

Maximizing Coverage for Mobile Robots While Conserving Energy

2012 ◽  
Author(s):  
John Broderick ◽  
Dawn Tilbury ◽  
Ella Atkins
Keyword(s):  
Optimal Control ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Mobile Robots ◽  
Spanning Tree ◽  
Trade Offs ◽  
Tree Methods ◽  
Reduce Energy Consumption ◽  
Point To Point ◽  
Time And Energy

This paper presents a method to compare area coverage paths in the context of energy efficiency. We examine cover-age paths created from the Boustrophedon Decomposition and Spanning Tree methods in an optimal control setting. Our cost function weights the force inputs to drive the robot and the currently uncovered region. We derive an optimal traversal of the path in a point-to-point manner. In particular, we introduce a meas function that represents the percentage of the area that is still to be visited. The effect of meas on the optimal traversal is derived. Trade-offs between area covered versus the time and energy required are presented. A simple trajectory modification allows the vehicle to continue moving through a turn to reduce energy consumption.

An Alternative for Trajectory Tracking in Mobile Robots Applying Differential Flatness

2013 ◽  
pp. 148-160
Author(s):  
Elkin Yesid Veslin Díaz ◽  
Jules G. Slama ◽  
Max Suell Dutra ◽  
Omar Lengerke Pérez ◽  
Hernán Gonzalez Acuña
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Trajectory Tracking ◽  
Differential Flatness ◽  
Boundary Values ◽  
Route Finding ◽  
Point To Point

One solution for trajectory tracking in a non-holonomic vehicle, like a mobile robot, is proposed in this chapter. Using the boundary values, a desired route is converted into a polynomial using a point-to-point algorithm. With the properties of Differential Flatness, the system is driven along this route, finding the necessary input values so that the system can perform the desired movement.

scholarly journals A Survey of Path Planning Algorithms for Mobile Robots

Vehicles ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 448-468
Author(s):  
Karthik Karur ◽  
Nitin Sharma ◽  
Chinmay Dharmatti ◽  
Joshua E. Siegel
Keyword(s):  
Path Planning ◽  
Embedded System ◽  
Mobile Robots ◽  
Optimal Algorithm ◽  
Constrained Systems ◽  
Autonomous Cars ◽  
Planning Algorithm ◽  
Planning Algorithms ◽  
Point To Point ◽  
Path Planning Algorithm

Path planning algorithms are used by mobile robots, unmanned aerial vehicles, and autonomous cars in order to identify safe, efficient, collision-free, and least-cost travel paths from an origin to a destination. Choosing an appropriate path planning algorithm helps to ensure safe and effective point-to-point navigation, and the optimal algorithm depends on the robot geometry as well as the computing constraints, including static/holonomic and dynamic/non-holonomically-constrained systems, and requires a comprehensive understanding of contemporary solutions. The goal of this paper is to help novice practitioners gain an awareness of the classes of path planning algorithms used today and to understand their potential use cases—particularly within automated or unmanned systems. To that end, we provide broad, rather than deep, coverage of key and foundational algorithms, with popular algorithms and variants considered in the context of different robotic systems. The definitions, summaries, and comparisons are relevant to novice robotics engineers and embedded system developers seeking a primer of available algorithms.

Belated Analyses of Three Credit-Based Adaptive Polling Algorithms

2016 ◽  
Vol 27 (05) ◽  
pp. 579-594
Author(s):  
Savio S. H. Tse
Keyword(s):  
Lower Bound ◽  
Spanning Tree ◽  
Arbitrary Point ◽  
Message Complexity ◽  
Worst Case ◽  
Average Case ◽  
Asynchronous Networks ◽  
Adaptive Polling ◽  
Point To Point ◽  
Optimal Lower Bound

We study the problem of credit-based adaptive polling in undirected arbitrary point-to-point asynchronous networks. Polling consists of two rounds, namely propagation (broadcast) and feedback (confirmation, response) rounds. By adaptive polling, a spanning tree of unknown topology is built dynamically during the propagation round, and feedback messages are free to choose their paths back to the initiator — a specific node who initiates the polling algorithm. The freedom in the feedback round relies on the use of credits in the propagation round. We re-visit three existing algorithms and analyse their average case communication bit complexities incurred by the credits in the propagation round, and these analyses match with the numerical results. We also give an optimal lower bound on the worst case bit message complexity for the case when the number of nodes in the network is unknown.

Sign in / Sign up

Export Citation Format

Share Document