Localization and obstacle avoidance in soccer competition of humanoid robot by gait and vision system

2019 ◽  
Vol 34 ◽  
Author(s):  
Shu-Yin Chiang ◽  
Jia-Huei Lu
Keyword(s):  
Obstacle Avoidance ◽  
Humanoid Robot ◽  
Vision System ◽  
Humanoid Robots ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Step Counting ◽  
Grid Points ◽  
Using Data ◽  
Image Pattern

Abstract In this study, we designed a localization and obstacle avoidance system for humanoid robots in the Federation of International Robot-soccer Association (FIRA) HuroCup united soccer competition event. The localization is implemented by using grid points, gait, and steps to determine the positions of each robot. To increase the localization accuracy and eliminate the accumulated distance errors resulting from step counting, the localization is augmented with image pattern matching using a system model. The system also enables the robot to determine the ball’s position on the field using a color model of the ball. Moreover, to avoid obstacles, the robots calculate the obstacle distance using data extracted from real-time images and determine a suitable direction for movement. With the integration of this accurate self-localization algorithm, ball identification scheme, and obstacle avoidance system, the robot team is capable of accomplishing the necessary tasks for a FIRA soccer game.

Vision-based obstacle avoidance system with fuzzy logic for humanoid robots

2016 ◽  
Vol 32 ◽  
Author(s):  
Shu-Yin Chiang
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Obstacle Avoidance ◽  
Humanoid Robot ◽  
Vision System ◽  
Humanoid Robots ◽  
Robot Motion ◽  
Connected Component ◽  
Open Platform ◽  
Connected Component Labeling

AbstractThis study presents the algorithm for a humanoid robot to accomplish an obstacle run in the FIRA HuroCup competition. It includes the integration of image processing and robot motion. DARwIn-OP (Dynamic Anthropomorphic Robot with Intelligence–Open Platform) was used as the humanoid robot, and it is equipped with a webcam as a vision system to obtain an image of what is in front of the robot. Image processing skills such as erosion, dilation, and eight-connected component labeling are applied to reduce image noise. Moreover, we use navigation grids with filters to avoid the obstacles. Fuzzy logic rules are used to implement the robot’s motion, allowing a humanoid robot to access any routes using obstacle avoidance to perform the tasks in the obstacle-run event.

The Development of Supervised Motion Learning and Vision System for Humanoid Robot

2019 ◽  
Vol 886 ◽  
pp. 188-193 ◽  
Author(s):  
Ssu Ting Lin ◽  
Jun Hu ◽  
Chia Hung Shih ◽  
Chiou Jye Huang ◽  
Ping Huan Kuo
Keyword(s):  
Humanoid Robot ◽  
Physical Mechanism ◽  
Learning Algorithm ◽  
Vision System ◽  
Humanoid Robots ◽  
Learning System ◽  
Automatic Learning ◽  
Swarm Optimization ◽  
Motion Learning ◽  
Important Research Topic

With the development of the concept of Industry 4.0, research relating to robots is being paid more and more attention, among which the humanoid robot is a very important research topic. The humanoid robot is a robot with a bipedal mechanism. Due to the physical mechanism, humanoid robots can maneuver more easily in complex terrains, such as going up and down the stairs. However, humanoid robots often fall from imbalance. Whether or not the robot can stand up on its own after a fall is a key research issue. However, the often used method of hand tuning to allow robots to stand on its own is very inefficient. In order to solve the above problems, this paper proposes an automatic learning system based on Particle Swarm Optimization (PSO). This system allows the robot to learn how to achieve the motion of rebalancing after a fall. To allow the robot to have the capability of object recognition, this paper also applies the Convolutional Neural Network (CNN) to let the robot perform image recognition and successfully distinguish between 10 types of objects. The effectiveness and feasibility of the motion learning algorithm and the CNN based image classification for vision system proposed in this paper has been confirmed in the experimental results.

A Study on Fuzzy Control of Humanoid Soccer Robot EFuRIO for Vision Control System and Walking Movement

2012 ◽  
Vol 16 (3) ◽  
pp. 444-452
Author(s):  
Indra Adji Sulistijono ◽  
◽  
Son Kuswadi ◽  
One Setiaji ◽  
Inzar Salfikar ◽  
...  
Keyword(s):  
Fuzzy Logic Control ◽  
Humanoid Robot ◽  
Vision System ◽  
Humanoid Robots ◽  
Soccer Robot ◽  
Balance Condition ◽  
Logic Control ◽  
Control Scheme ◽  
Vision Control ◽  
The Stability

Instability is one of the major defects in humanoid robots. Recently, various methods on the stability and reliability of humanoid robots have been studied actively. We propose a new fuzzy-logic control scheme for vision systems that would enable a robot to search for and to kick a ball towards an opponent goal. In this paper, a stabilization algorithm is proposed using the balance condition of the robot, which is measured using accelerometer sensors during standing and walking, and turning movement are estimated from these data. From this information the robot selects the appropriate motion pattern effectively. In order to generate the appropriate reaction in various body of robot situations, a fuzzy algorithm is applied in finding the appropriate angle of the joint from the vision system. The performance of the proposed algorithm is verified by searching for a ball, walking, turning tap and ball kicking movement experiments using an 18-DOF humanoid robot, called EFuRIO.

VISION-BASED OBSTACLE AVOIDANCE NAVIGATION WITH AUTONOMOUS HUMANOID ROBOTS FOR STRUCTURED COMPETITION PROBLEMS

2013 ◽  
Vol 10 (03) ◽  
pp. 1350021 ◽  
Author(s):  
CHUNG-HSIEN KUO ◽  
HUNG-CHYUN CHOU ◽  
SHOU-WEI CHI ◽  
YU-DE LIEN
Keyword(s):  
Obstacle Avoidance ◽  
Humanoid Robot ◽  
Ground Truth ◽  
Humanoid Robots ◽  
Visual Localization ◽  
Adult Size ◽  
Map Construction ◽  
Rule Approach ◽  
High Level ◽  
Autonomous Humanoid

Biped humanoid robots have been developed to successfully perform human-like locomotion. Based on the use of well-developed locomotion control systems, humanoid robots are further expected to achieve high-level intelligence, such as vision-based obstacle avoidance navigation. To provide standard obstacle avoidance navigation problems for autonomous humanoid robot researches, the HuroCup League of Federation of International Robot-Soccer Association (FIRA) and the RoboCup Humanoid League defined the conditions and rules in competitions to evaluate the performance. In this paper, the vision-based obstacle avoidance navigation approaches for humanoid robots were proposed in terms of combining the techniques of visual localization, obstacle map construction and artificial potential field (APF)-based reactive navigations. Moreover, a small-size humanoid robot (HuroEvolutionJR) and an adult-size humanoid robot (HuroEvolutionAD) were used to evaluate the performance of the proposed obstacle avoidance navigation approach. The navigation performance was evaluated with the distance of ground truth trajectory collected from a motion capture system. Finally, the experiment results demonstrated the effectiveness of using vision-based localization and obstacle map construction approaches. Moreover, the APF-based navigation approach was capable of achieving smaller trajectory distance when compared to conventional just-avoiding-nearest-obstacle-rule approach.

LOLA – a Performance Enhanced Humanoid Robot (LOLA – ein leistungsgesteigerter humanoider Roboter)

2007 ◽  
Vol 49 (4) ◽  
Author(s):  
Thomas Buschmann ◽  
Sebastian Lohmeier ◽  
Kolja Kühnlenz ◽  
Martin Buss ◽  
Heinz Ulbrich ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Vision System ◽  
Humanoid Robots ◽  
Lightweight Construction ◽  
Brushless Motors ◽  
Multibody Model ◽  
Accurate Localization ◽  
6 Degrees Of Freedom ◽  
And Control

SummaryHumanoid robots are perfectly suited for service applications, since their human-like shape allows them to easily access environments designed for humans. This paper presents the performance enhanced humanoid robot LOLA. The goal of the project is to realize fast, human-like and vision-guided walking. LOLA's hardware is characterized by lightweight construction, modular, multi-sensory joint design with brushless motors and an electronics architecture using decentralized joint controllers. Real-time walking control is realized by a hierarchical trajectory generation and control system. Hardware and control are designed using a comprehensive multibody model of the robot. LOLA is equipped with a novel multi-focal vision system with four cameras and 6 degrees-of-freedom. Multifocal situation-specific gaze control provides high perception quality, flexible reaction, and accurate localization and navigation in large and weakly structured environments.

Real-Time Navigation for a Humanoid Robot Using Particle Filter

2013 ◽  
Vol 284-287 ◽  
pp. 1914-1918
Author(s):  
Jacky Baltes ◽  
Chi Tai Cheng ◽  
Meng Cheng Lau ◽  
Andrés Espínola
Keyword(s):  
Path Planning ◽  
Particle Filter ◽  
Real Time ◽  
Humanoid Robot ◽  
Vision System ◽  
Empirical Evaluation ◽  
Humanoid Robots ◽  
Visual Navigation ◽  
Planning System ◽  
Localization System

This paper presents a practical real-time visual navigation system, including a vision system, a particle filter (PF) based localization system, and a path planning system, for humanoid robots in an indoor environment. A neural network (NN) converter system is used to solve the image distortion problem. The monocular vision system detects objects of interest in the scene, calculating their position in the image, and converting the position in the image to real world coordinates. The PF localization system estimates the current position by the robot’s motion model and corrects the estimated position by using feedback from the data gathered by the vision system. The path planning system determines the next motion based on the result of the localization system. This paper uses a tree-like path planning method which not only guides the robot to the destination but also avoids obstacles at the same time. The navigation method allows a user to assign several different target destinations to the robot simultaneously. The proposed method is implemented on a humanoid robot “ROBOTIS DARwIn-OP”, an open platform humanoid robot. The effectiveness of the system is demonstrated in an empirical evaluation.

Humans and humanoids

2018 ◽  
Author(s):  
Giorgio Metta
Keyword(s):  
Humanoid Robot ◽  
Robot Vision ◽  
Physical Space ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Biologically Inspired ◽  
Robot Interaction ◽  
Humanoid Robotics ◽  
Biomimetic Robot ◽  
Compliant Actuation

This chapter outlines a number of research lines that, starting from the observation of nature, attempt to mimic human behavior in humanoid robots. Humanoid robotics is one of the most exciting proving grounds for the development of biologically inspired hardware and software—machines that try to recreate billions of years of evolution with some of the abilities and characteristics of living beings. Humanoids could be especially useful for their ability to “live” in human-populated environments, occupying the same physical space as people and using tools that have been designed for people. Natural human–robot interaction is also an important facet of humanoid research. Finally, learning and adapting from experience, the hallmark of human intelligence, may require some approximation to the human body in order to attain similar capacities to humans. This chapter focuses particularly on compliant actuation, soft robotics, biomimetic robot vision, robot touch, and brain-inspired motor control in the context of the iCub humanoid robot.

DESIGN AND SIMULATION OF A 1-DOF ANTHROPOMORPHIC CLUTCHED ARM FOR HUMANOID ROBOTS

2010 ◽  
Vol 07 (01) ◽  
pp. 157-182 ◽  
Author(s):  
HAO GU ◽  
MARCO CECCARELLI ◽  
GIUSEPPE CARBONE
Keyword(s):  
Humanoid Robot ◽  
Humanoid Robots ◽  
Robot Arm ◽  
Dynamic Simulations ◽  
Suitable Combination ◽  
User Friendly

In this paper, problems for an anthropomorphic robot arm are approached for an application in a humanoid robot with the specific features of cost oriented design and user-friendly operation. One DOF solution is proposed by using a suitable combination of gearing systems, clutches, and linkages. Models and dynamic simulations are used both for designing the system and checking the operation feasibility.

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