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 A Multitasking-Oriented Robot Arm Motion Planning Scheme Based on Deep Reinforcement Learning and Twin Synchro-Control

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3515 ◽  
Author(s):  
Chuzhao Liu ◽  
Junyao Gao ◽  
Yuanzhen Bi ◽  
Xuanyang Shi ◽  
Dingkui Tian
Keyword(s):  
Reinforcement Learning ◽  
Motion Planning ◽  
Data Acquisition ◽  
Humanoid Robot ◽  
Data Acquisition System ◽  
Humanoid Robots ◽  
Acquisition System ◽  
Robot Arm ◽  
Digital Twin ◽  
Angle Data

Humanoid robots are equipped with humanoid arms to make them more acceptable to the general public. Humanoid robots are a great challenge in robotics. The concept of digital twin technology complies with the guiding ideology of not only Industry 4.0, but also Made in China 2025. This paper proposes a scheme that combines deep reinforcement learning (DRL) with digital twin technology for controlling humanoid robot arms. For rapid and stable motion planning for humanoid robots, multitasking-oriented training using the twin synchro-control (TSC) scheme with DRL is proposed. For switching between tasks, the robot arm training must be quick and diverse. In this work, an approach for obtaining a priori knowledge as input to DRL is developed and verified using simulations. Two simple examples are developed in a simulation environment. We developed a data acquisition system to generate angle data efficiently and automatically. These data are used to improve the reward function of the deep deterministic policy gradient (DDPG) and quickly train the robot for a task. The approach is applied to a model of the humanoid robot BHR-6, a humanoid robot with multiple-motion mode and a sophisticated mechanical structure. Using the policies trained in the simulations, the humanoid robot can perform tasks that are not possible to train with existing methods. The training is fast and allows the robot to perform multiple tasks. Our approach utilizes human joint angle data collected by the data acquisition system to solve the problem of a sparse reward in DRL for two simple tasks. A comparison with simulation results for controllers trained using the vanilla DDPG show that the designed controller developed using the DDPG with the TSC scheme have great advantages in terms of learning stability and convergence speed.

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.

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.

Mechatronic Design of ARC Humanoid Robot Open Platform: First Fully 3D Printed Kid-Sized Robot

2020 ◽  
Vol 17 (03) ◽  
pp. 2050010
Author(s):  
Saeed Saeedvand ◽  
Hadi S. Aghdasi ◽  
Jacky Baltes
Keyword(s):  
Humanoid Robot ◽  
Size Range ◽  
Robot Design ◽  
3D Printer ◽  
Wide Angle ◽  
Open Platform ◽  
3D Printed ◽  
Wide Angle Camera ◽  
Computational Resources ◽  
User Friendly

Although there are several popular and capable humanoid robot designs available in the kid-size range, they lack some important characteristics: affordability, being user-friendly, using a wide-angle camera, sufficient computational resources for advanced AI algorithms, and mechanical robustness and stability are the most important ones. Recent advances in 3D printer technology enables researchers to move from model to physical implementation relatively easy. Therefore, we introduce a novel fully 3D printed open platform humanoid robot design named ARC. In this paper, we discuss the mechanical structure and software architecture. We show the capabilities of the ARC design in a series of experimental evaluations.

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.

scholarly journals Differences between young and old users when interacting with a humanoid robot: a qualitative usability study

2018 ◽  
Vol 9 (1) ◽  
pp. 183-192 ◽  
Author(s):  
Ronit Feingold-Polak ◽  
Avital Elishay ◽  
Yonat Shahar ◽  
Maayan Stein ◽  
Yael Edan ◽  
...  
Keyword(s):  
Young Adults ◽  
Humanoid Robot ◽  
Motor Task ◽  
Humanoid Robots ◽  
Limited Information ◽  
Old Adults ◽  
Body Of Knowledge ◽  
People With Dementia ◽  
Touch Interaction ◽  
The Difference

Abstract With the aging of the population worldwide, humanoid robots are being used with an older population, e.g., stroke patients and people with dementia. There is a growing body of knowledge on how people interact with robots, but limited information on the difference between young and old adults in their preferences when interacting with humanoid robots and what factors influence these preferences.We developed a gamified robotic platform of a cognitive-motor task.We conducted two experiments with the following aims: to test how age, location of touch interaction (touching the robot’s tablet or hand), and embodied presence of a humanoid robot affect the motivation of different age-group users to continue performing a cognitive-motor task. A total of 60 participants (30 old adults and 30 young adults) took part in two experiments with the humanoid Pepper robot (Softbank robotics). Both old and young adults reported they enjoyed the interaction with the robot as they found it engaging and fun, and preferred the embodied robot over the non-embodied computer screen. This study highlights that in order for the experience of the user to be positive a personalization of the interaction according to the age, the needs of the user, the characteristics, and the pace of the task is needed.

Regenerative effects in the Sit-to-Stand and Stand-to-Sit movement

Robotica ◽  
2014 ◽  
Vol 33 (1) ◽  
pp. 107-126 ◽  
Author(s):  
Ronnie Joseph Wong ◽  
James Andrew Smith
Keyword(s):  
Energy Efficient ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
Gear Ratio ◽  
Scale Model ◽  
Hip Joints ◽  
Regenerative Effect ◽  
Sit To Stand ◽  
A Value ◽  
Nimh Battery

SUMMARYWhile Sit-to-Stand and Stand-to-Sit are routine activities and are crucial pre-requisites to walking and running their underlying dynamics are poorly understood. Furthermore, the potential for using these movements to regenerate energy in energy-sensitive devices such as orthoses, prostheses and humanoid robots has never been examined. Insights in this domain can lead to more energy-efficient prosthesis, orthosis and humanoid robot designs.OBJECTIVES: The objectives are two-fold: first, to determine how much energy can be regenerated during standard movements related to transitions between sitting and standing on a scale humanoid model and second, to determine if the chosen actuator could produce better results if the gear ratio were modified. This manuscript's main contribution to the literature is by showing which joint provides the most regenerative effect during transitions between sitting and standing.MODEL DESIGN AND IMPLEMENTATION: Joint trajectories from existing biomechanics trials of sitting and standing transitions were fed into a 1/10 scale model of a humanoid robot. The robot model, developed in MapleSim, is comprised of standard and off-the-shelf subcomponents, including amplifier, NiMH battery and Robotis Dynamixel RX-28 actuators.RESULTS: Using the RX-28 actuator, the ankle, knee and hip joints all show a degree of regenerative effects, the hip demonstrates the most dramatic levels during the transition from standing to sitting. This contrasts with recent publications which show that the knee has the most important regenerative effects during walking and running. It is also found that for under 3 degree trajectory error the regenerative effect is best for all joints when the gear ratio is increased from the RX-28's 193:1 value to a value of approximately 760:1 for the ankle, 630:1 for the knee and 600:1 for the hip.CONCLUSIONS: During transitions between sitting and standing the greatest potential for regeneration occurs in the hips. Therefore, systems designed to implement regenerative effects between sitting and standing need to include subsystems at the hip for maximum regenerative effects.

scholarly journals Humanoid Robots: Useful or Useless?

2015 ◽  
Vol 7 (11) ◽  
Author(s):  
Richard C Seals
Keyword(s):  
User Interface ◽  
Humanoid Robot ◽  
Touch Screen ◽  
Humanoid Robots ◽  
Potential Usefulness

The potential usefulness of a humanoid robot (Robothespian) was investigated by a group of six MSc students who chose to use this system for one of their oral assignments. A variety of methodologies were used by the student ranging from treating the Robothepsian mostly as a machine to an apparently fully interactive live conversation. The humanoid robot proved to be an interesting and stimulating approach but it did have problems with the user interface used (touch screen display) and that there was only one available.

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