The experimental humanoid robot H7: a research platform for autonomous behaviour

Author(s):  
Koichi Nishiwaki ◽  
James Kuffner ◽  
Satoshi Kagami ◽  
Masayuki Inaba ◽  
Hirochika Inoue

This paper gives an overview of the humanoid robot ‘H7’, which was developed over several years as an experimental platform for walking, autonomous behaviour and human interaction research at the University of Tokyo. H7 was designed to be a human-sized robot capable of operating autonomously in indoor environments designed for humans. The hardware is relatively simple to operate and conduct research on, particularly with respect to the hierarchical design of its control architecture. We describe the overall design goals and methodology, along with a summary of its online walking capabilities, autonomous vision-based behaviours and automatic motion planning. We show experimental results obtained by implementations running within a simulation environment as well as on the actual robot hardware.

Author(s):  
Joanne Pransky

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.


Author(s):  
Fredy Martinez ◽  
Edwar Jacinto ◽  
Fernando Martinez

This paper presents a low cost strategy for real-time estimation of the position of obstacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.


2018 ◽  
Vol 44 ◽  
pp. 00061
Author(s):  
Anna Jurga ◽  
Joanna Kuźma ◽  
Paweł Płuszka ◽  
Piotr Chmielewski ◽  
Edyta Bobrowska ◽  
...  

The article presents the concept of experimental research system to investigate aeroponic cultivation in microgravity condition. The main scientific objective is to define the forces acting in droplet-root system exposed to microgravity conditions especially the adhesion and cohesion phenomena. The concept of a research platform is presented in this paper and includes electrical, hydraulic and optical system.


Author(s):  
Terrence Fernando ◽  
Prasad Wimalaratne ◽  
Kevin Tan

Abstract This paper presents the design and implementation of a constraint-based virtual environment for supporting interactive assembly and maintenance tasks. The system architecture of the constraint-based virtual environment is based on the integration of components such as OpenGL Optimizer, Parasolid geometric kernel, a Constraint Engine and an Assembly Relationship Graph (ARG). The approach presented in this paper is based on pure geometric constraints. Techniques such as automatic constraint recognition, constraint satisfaction, constraint management and constrained motion are employed to support interactive assembly operations and realistic behaviour of assembly parts. The current system has been evaluated using two industrial case studies. This work is being carried out as a part of a research programme referred to as IPSEAM (Interactive Product Simulation Environment for Assessing Assembly and Maintainability), at the University of Salford.


Author(s):  
PEDRO TEODORO ◽  
MIGUEL AYALA BOTTO ◽  
CARLOS CARDEIRA ◽  
JORGE MARTINS ◽  
JOSÉ SÁ DA COSTA ◽  
...  

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