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.

DYNAMIC ROLL-AND-RISE MOTION BY AN ADULT-SIZE HUMANOID ROBOT

2004 ◽  
Vol 01 (03) ◽  
pp. 497-516 ◽  
Author(s):  
YASUO KUNIYOSHI ◽  
YOSHIYUKI OHMURA ◽  
KOJI TERADA ◽  
AKIHIKO NAGAKUBO
Keyword(s):  
Critical Points ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
The Body ◽  
Whole Body ◽  
Adult Size ◽  
Constrained Motion ◽  
Goal State ◽  
Trade Offs ◽  
Alternative Approach

Whole-body dynamic actions under various contacts with the environment will be very important for future humanoid robots to support human tasks in unstructured environments. Such skills are very difficult to realize using the standard motion control methodology based on asymptotic convergence to the successive desired states. An alternative approach would be to exploit the passive dynamics of the body under constrained motion, and to navigate through multiple dynamics by imposing the least control in order to robustly reach the goal state. As a first example of such a strategy, we propose and investigate a "Roll-and-Rise" motion. This is a fully dynamic whole-body task including underactuated motion whose state trajectory is insoluble, and unpredictable perturbations due to complex contacts with the ground. First, we analyze the global structure of Roll-and-Rise motion. Then the critical points are analyzed using simplified models and simulations. The results suggest a non-uniform control strategy which focuses on sparse critical points in the global phase space, and allows deviations and trade-offs at other parts. Finally, experiments with a real adult-size humanoid robot are successfully carried out. The robot rose from a flat-lying posture to a crouching posture within 2 seconds.

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.

COLLABORATING WITH HUMANOID ROBOTS IN SPACE

2005 ◽  
Vol 02 (02) ◽  
pp. 181-201 ◽  
Author(s):  
DONALD SOFGE ◽  
MAGDALENA BUGAJSKA ◽  
J. GREGORY TRAFTON ◽  
DENNIS PERZANOWSKI ◽  
SCOTT THOMAS ◽  
...  
Keyword(s):  
Perspective Taking ◽  
Humanoid Robot ◽  
Spatial Reasoning ◽  
Cognitive Model ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Joint Effort ◽  
Robot Interaction ◽  
Gesture Understanding ◽  
High Level

One of the great challenges of putting humanoid robots into space is developing cognitive capabilities for the robots with an interface that allows human astronauts to collaborate with the robots as naturally and efficiently as they would with other astronauts. In this joint effort with NASA and the entire Robonaut team, we are integrating natural language and gesture understanding, spatial reasoning incorporating such features as human–robot perspective taking, and cognitive model-based understanding to achieve a high level of human–robot interaction. Building greater autonomy into the robot frees the human operator(s) from focusing strictly on the demands of operating the robot, and instead allows the possibility of actively collaborating with the robot to focus on the task at hand. By using shared representations between the human and robot, and enabling the robot to assume the perspectives of the human, the humanoid robot may become a more effective collaborator with a human astronaut for achieving mission objectives in space.

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.

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.

scholarly journals User-centred design of humanoid robots’ communication

2020 ◽  
Vol 12 (1) ◽  
pp. 58-73
Author(s):  
Sofia Thunberg ◽  
Tom Ziemke
Keyword(s):  
Mental Models ◽  
Participatory Design ◽  
Humanoid Robot ◽  
State Of The Art ◽  
Design Method ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Design Concepts ◽  
Design Ideas

AbstractInteraction between humans and robots will benefit if people have at least a rough mental model of what a robot knows about the world and what it plans to do. But how do we design human-robot interactions to facilitate this? Previous research has shown that one can change people’s mental models of robots by manipulating the robots’ physical appearance. However, this has mostly not been done in a user-centred way, i.e. without a focus on what users need and want. Starting from theories of how humans form and adapt mental models of others, we investigated how the participatory design method, PICTIVE, can be used to generate design ideas about how a humanoid robot could communicate. Five participants went through three phases based on eight scenarios from the state-of-the-art tasks in the RoboCup@Home social robotics competition. The results indicate that participatory design can be a suitable method to generate design concepts for robots’ communication in human-robot interaction.

scholarly journals Obstacle Avoidance in Groping Locomotion of a Humanoid Robot

10.5772/5783 ◽  
2005 ◽  
Vol 2 (3) ◽  
pp. 26 ◽  
Author(s):  
Hanafiah Yussof ◽  
Mitsuhiro Yamano ◽  
Yasuo Nasu ◽  
Kazuhisa Mitobe ◽  
Masahiro Ohka
Keyword(s):  
Control System ◽  
Obstacle Avoidance ◽  
Force Control ◽  
Humanoid Robot ◽  
Flat Surface ◽  
Rotation Angle ◽  
Basic Research ◽  
Orientation Data ◽  
Robotic Arms ◽  
End Effectors

This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robot's control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robot's leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a wall's surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.

The Pransky interview: Dr Jun Ho Oh, Professor and Director of Humanoid Robot Research Center, KAIST; Cofounder, Rainbow Robotics Co.

2017 ◽  
Vol 44 (6) ◽  
pp. 695-699
Author(s):  
Joanne Pransky
Keyword(s):  
Mechanical Engineering ◽  
Humanoid Robot ◽  
Industrial Robot ◽  
Science And Technology ◽  
Vice President ◽  
Humanoid Robots ◽  
Real Time Control ◽  
Commercial Development ◽  
Content Type ◽  
The University

Purpose The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD-turned-entrepreneur regarding the commercialization and challenges of bringing a technological invention to market. This paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Jun Ho Oh, Professor of Mechanical Engineering at the Korea Advanced Institute of Science and Technology (KAIST) and Director of KAIST’s Hubolab. Determined to build a humanoid robot in the early 2000s to compete with Japan’s humanoids, Dr Oh and KAIST created the KHR1. This research led to seven more advanced versions of a biped humanoid robot and the founding of the Robot for Artificial Intelligence and Boundless Walking (Rainbow) Co., a professional technological mechatronics company. In this interview, Dr Oh shares the history and success of Korea’s humanoid robot research. Findings Dr Oh received his BSc in 1977 and MSc in Mechanical Engineering in 1979 from Yonsei University. Oh worked as a Researcher for the Korea Atomic Energy Research Institute before receiving his PhD from the University of California (UC) Berkeley in mechanical engineering in 1985. After his PhD, Oh remained at UC Berkeley to do Postdoctoral research. Since 1985, Oh has been a Professor of Mechanical Engineering at KAIST. He was a Visiting Professor from 1996 to 1997 at the University of Texas Austin. Oh served as the Vice President of KAIST from 2013-2014. In addition to teaching, Oh applied his expertise in robotics, mechatronics, automatic and real-time control to the commercial development of a series of humanoid robots. Originality/value Highly self-motivated and always determined, Dr Oh’s initial dream of building the first Korean humanoid bipedal robot has led him to become one of the world leaders of humanoid robots. He has contributed widely to the field over the nearly past two decades with the development of five versions of the HUBO robot. Oh led Team KAIST to win the 2015 DARPA Robotics Challenge (DRC) and a grand prize of US$2m with its humanoid robot DRC-HUBO+, beating 23 teams from six countries. Oh serves as a robotics policy consultant for the Korean Ministry of Commerce Industry and Energy. He was awarded the 2016 Changjo Medal for Science and Technology, the 2016 Ho-Am Prize for engineering, and the 2010 KAIST Distinguished Professor award. He is a member of the Korea Academy of Science and Technology.

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