COAA* — An Optimized Obstacle Avoidance and Navigational Algorithm for UAVs Operating in Partially Observable 2D Environments

2021 ◽  
pp. 1-16
Author(s):  
Jun Jet Tai ◽  
Swee King Phang ◽  
Felicia Yen Myan Wong
Keyword(s):  
Obstacle Avoidance ◽  
Global Minimum ◽  
Autonomous Robots ◽  
Real Life ◽  
Widespread Implementation ◽  
Heavy Lift ◽  
Solution Methods ◽  
Computational Requirement ◽  
Partially Observable ◽  
Online Methods

Obstacle avoidance and navigation (OAN) algorithms typically employ offline or online methods. The former is fast but requires knowledge of a global map, while the latter is usually more computationally heavy in explicit solution methods, or is lacking in configurability in the form of artificial intelligence (AI) enabled agents. In order for OAN algorithms to be brought to mass produced robots, more specifically for multirotor unmanned aerial vehicles (UAVs), the computational requirement of these algorithms must be brought low enough such that its computation can be done entirely onboard a companion computer, while being flexible enough to function without a prior map, as is the case of most real life scenarios. In this paper, a highly configurable algorithm, dubbed Closest Obstacle Avoidance and A* (COAA*), that is lightweight enough to run on the companion computer of the UAV is proposed. This algorithm frees up from the conventional drawbacks of offline and online OAN algorithms, while having guaranteed convergence to a global minimum. The algorithms have been successfully implemented on the Heavy Lift Experimental (HLX) UAV of the Autonomous Robots Research Cluster in Taylor’s University, and the simulated results match the real results sufficiently to show that the algorithm has potential for widespread implementation.

scholarly journals A Triboelectric-Based Artificial Whisker for Reactive Obstacle Avoidance and Local Mapping

Research ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Peng Xu ◽  
Xingyu Wang ◽  
Siyuan Wang ◽  
Tianyu Chen ◽  
Jianhua Liu ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Robots ◽  
Tactile Sensor ◽  
Triboelectric Nanogenerator ◽  
Tactile Sensors ◽  
Biologically Inspired ◽  
External Stimulation ◽  
Autonomous Surface Vehicles ◽  
Electrostatic Induction ◽  
Contact Position

Since designing efficient tactile sensors for autonomous robots is still a challenge, this paper proposes a perceptual system based on a bioinspired triboelectric whisker sensor (TWS) that is aimed at reactive obstacle avoidance and local mapping in unknown environments. The proposed TWS is based on a triboelectric nanogenerator (TENG) and mimics the structure of rat whisker follicles. It operates to generate an output voltage via triboelectrification and electrostatic induction between the PTFE pellet and copper films (0.3 mm thickness), where a forced whisker shaft displaces a PTFE pellet (10 mm diameter). With the help of a biologically inspired structural design, the artificial whisker sensor can sense the contact position and approximate the external stimulation area, particularly in a dark environment. To highlight this sensor’s applicability and scalability, we demonstrate different functions, such as controlling LED lights, reactive obstacle avoidance, and local mapping of autonomous surface vehicles. The results show that the proposed TWS can be used as a tactile sensor for reactive obstacle avoidance and local mapping in robotics.

Fuzzy MCDM Approach for Make or Buy Decision Problem

2014 ◽  
pp. 978-995 ◽  
Author(s):  
Ferhan Çebi ◽  
İrem Otay ◽  
Dilay Çelebi
Keyword(s):  
Decision Problem ◽  
Real Life ◽  
Fundamental Question ◽  
Multi Criteria Decision Making ◽  
Manufacturing Strategy ◽  
Weighting Method ◽  
Second Stage ◽  
Solution Methods ◽  
Simple Additive Weighting ◽  
A Company

Make or buy decision answers a fundamental question in the development of a manufacturing strategy. It requires consideration of both quantitative and qualitative factors diverging in a broad range. This study presents a two-stage decision model which incorporates fuzzy multi-criteria decision making methods to support make or buy decision of a company operating in the wood building products sector. The first stage comprises fuzzy SAW (Simple Additive Weighting) method to evaluate the decision on market entry, then the second stage integrates fuzzy SAW and fuzzy VIKOR (Multi-criteria optimization and compromise solution) methods to evaluate sourcing options. Proposed approach is demonstrated on an example invoked from a real-life problem. Then, sensitivity analysis is conducted to test the robustness of the models.

The multi resource leveling and materials procurement problem: an integrated approach

2020 ◽  
Vol 27 (9) ◽  
pp. 2135-2161
Author(s):  
Hessa Almatroushi ◽  
Moncer Hariga ◽  
Rami As'ad ◽  
AbdulRahman Al-Bar
Keyword(s):  
Renewable Resources ◽  
Project Scheduling ◽  
Lot Sizing ◽  
Real Life ◽  
Integrated Approach ◽  
Project Schedule ◽  
Sequential Approach ◽  
Content Type ◽  
Ordering Policy ◽  
Solution Methods

PurposeThis paper proposes an integrated approach that seeks to jointly optimize project scheduling and material lot sizing decisions for time-constrained project scheduling problems.Design/methodology/approachA mixed integer linear programming model is devised, which utilizes the splitting of noncritical activities as a mean toward leveling the renewable resources. The developed model minimizes renewable resources leveling costs along with consumable resources related costs, and it is solved using IBM ILOG CPLEX optimization package. A hybrid metaheuristic procedure is also proposed to efficiently solve the model for larger projects with complex networks structure.FindingsThe results confirmed the significance of the integrated approach as both the project schedule and the material ordering policy turned out to be different once compared to the sequential approach under same parameter settings. Furthermore, the integrated approach resulted in substantial total costs reduction for low values of the acquiring and releasing costs of the renewable resources. Computational experiments conducted over 240 test instances of various sizes, and complexities illustrate the efficiency of the proposed metaheuristic approach as it yields solutions that are on average 1.14% away from the optimal ones.Practical implicationsThis work highlights the necessity of having project managers address project scheduling and materials lot sizing decisions concurrently, rather than sequentially, to better level resources and minimize materials related costs. Significant cost savings were generated through the developed model despite the use of a small-scale example which illustrates the great potential that the integrated approach has in real life projects. For real life projects with complex network topology, practitioners are advised to make use of the developed metaheuristic procedure due to its superior time efficiency as compared to exact solution methods.Originality/valueThe sequential approach, wherein a project schedule is established first followed by allocating the needed resources, is proven to yield a nonoptimized project schedule and materials ordering policy, leading to an increase in the project's total cost. The integrated approach proposed hereafter optimizes both decisions at once ensuring the timely completion of the project at the least possible cost. The proposed metaheuristic approach provides a viable alternative to exact solution methods especially for larger projects.

Brief Report: Results of Third-Grade Students in a Reform Curriculum on the Illinois State Mathematics Test

1997 ◽  
Vol 28 (2) ◽  
pp. 237-242
Author(s):  
William M. Carroll
Keyword(s):  
Small Groups ◽  
Real Life ◽  
Chicago School ◽  
Alternative Methods ◽  
Second Grade ◽  
National Council ◽  
Elementary Curriculum ◽  
Reform Curriculum ◽  
Solution Methods ◽  
Traditional Curricula

Over the past decade, there has been a call for major reforms in mathematics education, from classrooms where students memorize facts and practice algorithms to classrooms in which reasoning and understanding are given more emphasis (National Council of Teachers of Mathematics [NCTM], 1989, 1991, 1995). In response, a number of curricula have been developed that attempt to meet this vision. One reform curriculum in widespread usage is the University of Chicago School Mathematics Project's (UCSMP) elementary curriculum, Everyday Mathematics. In the UCSMP curriculum, students work in small groups exploring mathematics in real-life contexts, using calculators, manipulatives, and other mathematical tools from kindergarten onward. In contrast to traditional curricula, students are encouraged to use these tools or to “invent” their own computational algorithms to solve problems, and the sharing of their alternative solution methods is a regular part of class discussions. Additionally, problems are nearly always application-based and never presented as sets of symbolic problems. For example, in a second-grade UCSMP lesson, students are given a picture depicting various animals and their heights or lengths. During this activity, students work in small groups to construct number stories that compare the animal heights and then to find a solution method. In the follow-up discussion, students share their stories and solution procedures and offer alternative methods.

scholarly journals COG-DICE: An Algorithm for Solving Continuous-Observation Dec-POMDPs

2017 ◽  
Author(s):  
Madison Clark-Turner ◽  
Christopher Amato
Keyword(s):  
Markov Decision Process ◽  
Real World ◽  
Decision Process ◽  
Extended Version ◽  
Continuous Observation ◽  
Solution Methods ◽  
Markov Decision ◽  
Multi Agent ◽  
Partially Observable Markov ◽  
Partially Observable

The decentralized partially observable Markov decision process (Dec-POMDP) is a powerful model for representing multi-agent problems with decentralized behavior. Unfortunately, current Dec-POMDP solution methods cannot solve problems with continuous observations, which are common in many real-world domains. To that end, we present a framework for representing and generating Dec-POMDP policies that explicitly include continuous observations. We apply our algorithm to a novel tagging problem and an extended version of a common benchmark, where it generates policies that meet or exceed the values of equivalent discretized domains without the need for finding an adequate discretization.

scholarly journals On the Benefits of Providing Timely Information in Ticket Queues with Balking and Calling Times

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2753
Author(s):  
Gabi Hanukov ◽  
Michael Hassoun ◽  
Oren Musicant
Keyword(s):  
Performance Measures ◽  
Traffic Congestion ◽  
Real Life ◽  
Time Loss ◽  
Wide Range ◽  
New Type ◽  
Expected Waiting Time ◽  
Partially Observable ◽  
Steady State Probabilities ◽  
Different Levels

We study a phenomenon causing server time loss in ticket queues with balking and calling time. A customer who balks from the queue after printing a ticket leaves a virtual entity in the queue that requires server time to be cleared. The longer the queue, the larger the proportion of customers abandoning their place, and the larger the server time loss due to calling customers that left the queue. The solution is suggested by giving the customer the best possible estimate of her expected waiting time before printing a ticket, thus ensuring that, if she balks, no number in the queue is created that will waste server time. Although partially observable ticket queues have been studied in the literature, the addition of a calling time for absent customers creates a new type of problem that has been observed in real life but has not been formally addressed yet. We analyze this stochastic system, formulate its steady state probabilities, and calculate the system’s performance measures. The analytical solution provided here is robust and can be applied to a wide range of customers’ behavior functions. Finally, numerical analysis is performed that demonstrates the benefits of providing timely information to customers for different levels of traffic congestion.

The Secant Method: Global Trajectory Planning With Variable Radius, Solid Obstacles

2018 ◽  
Author(s):  
Konrad J. Ahlin ◽  
Nader Sadegh ◽  
Ai-Ping Hu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Global Minimum ◽  
Dimensional Space ◽  
Variable Radius ◽  
Control Scheme ◽  
Solid Obstacles ◽  
Global Trajectory ◽  
Unique Potential ◽  
Robotic Applications

Artificial Potential Field (APF) theory is a unique branch of robotic path planning, which could be capable of handling the need for high dimensional robotic obstacle avoidance. However, APF theories have general performance issues which often make them undesirable in application. This research analyzes the Secant Approach; an algorithm developed to follow the APF style of path planning, but which has guaranteed convergence and obstacle avoidance properties in n-dimensional space. Using a unique potential function, the Secant Approach can guarantee a global minimum at the target while provably eliminating local minimums at other locations. Also, a control scheme has been developed which has guaranteed convergence properties. The Secant Approach is therefore capable of guiding various forms of robotic applications to target positions in n-dimensional space, making the theory a powerful path planning tool. This analysis examines the structure of the Secant Approach and extends the theory to include variable radius, solid obstacles.

A Mobile Robot Obstacle Avoidance Using Fuzzy Logic and Model Predictive Control

2014 ◽  
Vol 548-549 ◽  
pp. 922-927
Author(s):  
Bayanjargal Baasandorj ◽  
Aamir Reyaz ◽  
Park Joung Ho ◽  
Cha Wang Cheol ◽  
Deok Jin Lee ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Model Predictive Control ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Predictive Control ◽  
Real Life ◽  
Dynamic Environment ◽  
Logic Control ◽  
Microwave Sensor ◽  
Very High

This paper presents a method of solving the problem of mobile robot Obstacle avoidance and path planning in an unknown dynamic environment. A linear model of the two-wheeled nonholonomic robot controlled using Model predictive control controller. For obstacle avoidance Fuzzy logic control is used. The ultrasonic sensors are used for positioning and identifying an obstacle. The proposed method is successfully tested in simulations. Obstacle avoiding technique is very useful in real life, this technique can also use as a vision belt of blind people by changing the IR sensor by a kinetic sensor ,which is on type of microwave sensor whose sensing range is very high and the output of this sensor vary in according to the object position changes.

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