Robot Competition Research Articles

A Reasonable Path Planning via Path Energy Minimization

This paper presents a path planning method by path energy minimizing that enables mobile robots to move smoothly in the real world with optimizing path shape for shortest distance or minimum curvature. It also enables robots to travel safely toward a destination because pedestrian motion prediction is embedded in path planning. This path planning method is based on problems experienced in a robot competition called Tsukuba Challenge. The problems involved nonsmooth motion arising from finite path patterns in A* algorithm, stuck motion arising from frequently path switching, and near misses arising from nonpredictive planning. Our path planning method minimizes pathshape energy defined as the connection between path points. Minimizing energy provides smooth paths and avoids path switching. We propose a path planning method with prediction of dynamic obstacle motion embedded to avoid near misses. Experimental results showed improvements in solving these problems.

DLR SpaceBot Cup 2013: A Space Robotics Competition

In November 2013, the German Aerospace Center (DLR) in Bonn hosted the SpaceBot Cup, Germany’s first of its kind space robotics competition. The scenario is set in a planetary exploration environment with some manipulation tasks. Ten entrants had eight month to define, develop, and build robotic systems and the according ground station setup to conduct a remote testbed mission. Then, the robotic element(s) were deployed onto a sparsely known planetary surface and had to conduct exploration of the environment, find and collect two artificial objects, and mount them to a third object. Communication between ground control station and planetary surface was limited and impaired by delay, making autonomous functionality crucial for the success of the mission. In this report, the motivation, scenario, tasks, and final competition event of the DLR SpaceBot Cup 2013 are presented.

Robust and Reliable Microtechnology Research and Education through the Mobile Microrobotics Challenge [Competitions

Inspired by the success of Robocup [1], the U.S. National Institute of Standards and Technology (NIST) [2] proposed a robot competition at the microscale-the Mobile Microrobotics Challenge (MMC). Microrobots for this competition utilize microelectromechanical system technology and are actuated using advanced control systems.

Self-localization Method of Omni-directional Soccer Robot Based on Quantum Immune Algorithm

In order to more effectively solve self-localization problem for soccer robot, this paper introduces a selflocalization method that is an optimization algorithm based on Quantum Immune Algorithm (QIA). A type of quantum algorithm encoding form is used which is the Bloch spherical coordinate encoding form. It can both guarantee the diversity of initial population. The immune operation can reduce the probability that the QIA gets local optimal solution. This algorithm is combined with white line localization method, and by means of the feature point matching method finally determines the robot’s pose in the field. Simulation experiments and contrasts in Xi’an University of Science and Technology of soccer robot lab show that this method not only improves the global localization accuracy of the mobile robot, but also enhances its real-time. The actual application performance test can verify the feasibility and stability of this self-localization method. In 2011 and 2012, we all ranked the first place RoboCup middle-sized soccer robot league in Educational Robot Competition in China. The Educational Robot Competition is one of the China major robotic event. These prizes indicate that the QIA combined with white line method has superiority in solving the self-localization problem for soccer robot.

Micromouse Solve Maze Based on Flood-Fill Algorithm

Micromouse championship is an international robotics competition is an event where small robot micromouse solves a 16x16 maze. Use center rule + straight-right rule the micro-mouse can quickly explore the unknown maze and find their way from a predetermined starting cell to the central area of the maze, then back to the starting cell. Map out the maze and use flood-fill algorithm to find an optimal route from the starting cell to the center cell, the micromouse will run that route in the shortest possible time.

2013年(第八屆)工業機器人競賽成績

2013年(第八屆)工業機器人競賽成績

2014 (9th) Industrial Robot Competition

2014 (9th) Industrial Robot Competition

Lessons Learned in a Ball Fetch-And-Carry Robotic Competition

Lessons Learned in a Ball Fetch-And-Carry Robotic Competition

エンジニアリング・デザイン教育としてのNHK高専ロボコン

エンジニアリング・デザイン教育としてのNHK高専ロボコン

Robotic Competitions: Teaching Robotics and Real-Time Programming with LEGO Mindstorms

A laboratory activity started a few years ago within a course of Foundation of Industrial Robotics for the Master Degree in Automation Engineering at the Engineering School of the University of Bologna. The goals were on one side to drive students to acquire practical knowledge on mobile robotics, on the other to teach them how to write efficient code for real time control of automatic machines and robots. The tasks assigned to the students required them to mechanically design and program autonomous robots to be used in a competition among teams. Because of its low-cost, the modularity and the possibility of building several different devices, the Lego Mindstorms Kit has been adopted. With respect to the software, the Java-based firmware LeJOS has been selected as a tool to teach how to develop structured software. The experience has being very positive both for the students and the teaching staff. Besides acquiring many technical skills, the students felt involved in practical activities, thus increasing their interest for the subject.

Factors Associated With Adoption of Robotic Surgical Technology in US Hospitals and Relationship to Radical Prostatectomy Procedure Volume

Robotic technology has diffused rapidly despite high costs and limited additive reimbursement by major payers. We aimed to identify the factors associated with hospitals' decisions to adopt robotic technology and the consequences of these decisions. This observational study used data on hospitals and market areas from 2005 to 2009. Included were hospitals in census-based statistical areas within states in the State Inpatient Database that participated in the American Hospital Association annual surveys and performed radical prostatectomies. The likelihood that a hospital would acquire a robotic facility and the rates of radical prostatectomy relative to the prevalence of robots in geographic market areas were assessed using multivariable analysis. Hospitals in areas where a higher proportion of other hospitals had already acquired a robot were more likely to acquire one (P=0.012), as were those with more than 300 beds (P<0.0001) and teaching hospitals (P<0.0001). There was a significant association between years with a robot and the change in the number of radical prostatectomies (P<0.0001). More radical prostatectomies were performed in areas where the number of robots per 100,000 men was higher (P<0.0001). Adding a single robot per 100,000 men in an area was associated with a 30% increase in the rate of radical prostatectomies. Local area robot competition was associated with the rapid spread of robot technology in the United States. Significantly more radical prostatectomies were performed in hospitals with robots and in market areas of hospitals with robotic technology.

A Localization Method Based on Map-Matching and Particle Swarm Optimization

This paper presents a novel localization method for small mobile robots. The proposed technique is especially designed for the [email protected], a new robotic competition which is started in Lisbon in 2011. The real-time localization technique resorts to low-cost infra-red sensors, a map-matching method and an Extended Kalman Filter (EKF) to create a pose tracking system that performs well. The sensor information is continuously updated in time and space according to the expected motion of the robot. Then, the information is incorporated into the map-matching optimization in order to increase the amount of sensor information that is available at each moment. In addition, the Particle Swarm Optimization (PSO) relocates the robot when the map-matching error is high, meaning that the map-matching is unreliable and the robot gets lost. The experiments presented in this paper prove the ability and accuracy of the presented technique to locate small mobile robots for this competition. Extensive results show that the proposed method presents an interesting localization capability for robots equipped with a limited amount of sensors, but also less reliable sensors.

A real-time simple light detection application for a flying robot in extreme noise and interference

In this work, a real-time vision-based algorithm has been developed and implemented on a flying robot, in order to detect and identify a light beacon in the presence of excessive colored noise and interference. Starting from very basic and simple image analysis techniques including color histograms, filtering techniques, and color space analyses, typical pixel-based characteristics or a model of the light beacon has been progressively established. It has been found that not only are various color space-based characteristics significant, but also the relationships between various channels across different color spaces are of great consequence, in a beacon detection problem, specifically referring to a blue light-emitting diode. A block-based search algorithm comprising of multiple thresholds and linear confidence level calculation has been implemented to search established model characteristics in real-time video image data. During implementation, once excessive noise was encountered during flight tests, a simple and low cost noise and interference filter was developed. This filter very effectively handled all noise encountered in real time. The proposed work was successfully implemented and utilized on GeorgiaTech’s participating aircraft for the International Aerial Robotics Competition by Association for Unmanned Vehicle Systems International for detection of a blue light-emitting diode problem. Major contributions of this work include establishing a multiple threshold search and detection algorithm based on not only various color channels but also their relationships and handling of as much as 40% noisy or interfered video data with successful practical implementation and demonstration of proposed approach.

Guest editors introduction: special issue on Inductive Logic Programming (ILP 2012)

This issue contains selected papers from ILP 2012: the 22nd International Conference on Inductive Logic Programming held in Dubrovnik, Croatia on September 17–19, 2012. Out of the original 47 submissions to the conference, the authors of 8 selected peer-reviewed papers were invited to submit a revised and extended version for this special issue. As a result of an additional peer review adopting the journal criteria, 5 of these papers were finally accepted. The assorted papers demonstrate the vitality of current ILP research applied in challenging applications (here, object recognition), augmenting its logical foundations (metainterpretative learning, interpretation dynamics), and combined with extra-logical machinelearning techniques (neural networks, Bayes nets). In particular, the paper “Plane-based Object Categorization using Relational Learning” by R. Farid and C. Sammut, which won the best student-paper prize kindly sponsored by this journal, explores the hypothesis that relational description for classes of 3D objects can be built for robust object categorization in a real robotic application. Labelled sets of planes from 3D point clouds gathered during the RoboCup Rescue Robot competition are used as examples for an ILP system. The results show that ILP can be successfully applied to recognize objects encountered by a robot especially in an urban search and rescue environment. The article “Meta-interpretive Learning: Application to Grammatical Inference” by S.H. Muggleton, D. Lin, N. Pahlavi and A. Tamaddoni-Nezhad develops a framework in

Biped Walking Robot Gait Planning Research

This paper uses biped walking robot as the research object, and designs robots original system, based on the requirements of Biped Walking Robot Competition of China. According to the biped walking robots characteristics of multi-joints, many degrees of freedom, multivariable, strong coupling and nonlinearity [, we can build system model using the Denavi - Hartenberg coordinate, describe the system model by the homogeneous coordinate transformation theory, and then plan on system gait based on ZMP stability . Finally, we can solve for the joint trajectory of the system by using computer-aided software.

Different World Views: STEM Students and Student Affairs

Different World Views: STEM Students and Student Affairs

Plane-based object categorisation using relational learning

We use Inductive Logic Programming (ILP) to learn classifiers for generic object recognition from point clouds, as generated by 3D cameras, such as the Kinect. Each point cloud is segmented into planar surfaces. Each subset of planes that represents an object is labelled and predicates describing those planes and their relationships are used for learning. Our claim is that a relational description for classes of 3D objects can be built for robust object categorisation in real robotic application. To test the hypothesis, labelled sets of planes from 3D point clouds gathered during the RoboCup Rescue Robot competition are used as positive and negative examples for an ILP system. The robustness of the results is evaluated by 10-fold cross validation. In addition, common household objects that have curved surfaces are used for evaluation and comparison against a well-known non-relational classifier. The results show that ILP can be successfully applied to recognise objects encountered by a robot especially in an urban search and rescue environment.

An Improved Hardware Design and Navigation Optimization Algorithm for Line Following Robot

The traditional line following navigation still plays an important role because of simple design and low cost. We have designed and tested a line follower robot and attended line follower robots competition. In order to address the common issues in the traditional robot line following navigation technology, such as weak environmental adaptability and vulnerability to the external ambient light, an improved hardware design and a new line following navigation optimization algorithm are proposed. The experiment results show that it improves the robustness and stability of the line following navigation robot control.

Exploration and mapping with autonomous robot teams

The MAGIC 2010 robot competition showed how well multi-robot teams can work with human teams in urban search.

A Study of Robot Car Positioning System in Small Area Based on Optical Mouse Sensor

For robot car, positioning or finding coordinate of robot are important in robot competition. Because which position a robot locates will decide which way it will go or which operation it will perform. How to position accurately becomes a key technology for robot system. Most of the robot positioning systems in competition depends on some special assisted black lines or dots on the competition site. However, in order to enhance the robot design, cancel those assisted lines becomes a new trend. Without those assisted lines, we must develop a new positioning technology to face an environment without any assisted lines. In this paper, we use both Arduino microprocessor and optical mouse sensor to design an optical positioning system for robot. We install an optical mouse sensor in the bottom of robot. When the robot moves, the mouse sensor will return the raw data of movement vector. The middle device Arduino will analyze the movement vector base on previous coordinate and finds the new coordinate of robot. The robot is built by the Lego NXT system and is connected to the Arduino system by I2C interface. In robot, we can build a digitalized map of competition site in advanced. Then it can continuously read the new coordinate from Arduino while moving, and decide which way to go or perform some operation.