Network-based Humanoid ‘MAHRU’ as Ubiquitous Robotic Companion

You, Bum-Jae; Kim, Doik; Kim, Chang-Hwan; Oh, Yonghwan; Jeong, Mun-Ho; Oh, Sang-Rok

doi:10.3182/20080706-5-kr-1001.00124

“…It also has an array of four laser scanners that provides clouds of 3D points in the surrounding environment. MAHRU [26] (Figure 4i) is a network-based humanoid robot with 35 DOF, including 6-DOFs for each arm and 4-DOFs for each hand. It also has two 6-DOFs legs, a stereo camera is mounted on the head, a microphone and four force sensors allow the robots to physically interact with the environment.…”

Section: Overview Of the Resultsmentioning

confidence: 99%

Human-Like Arm Motion Generation: A Review

Gulletta¹,

Erlhagen²,

Bicho³

2020

Preprint

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In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analysed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioural and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

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“…Moreover, it has an array of four laser scanners that provides clouds of 3D points in the surrounding environment. MAHRU [26] (Figure 4i) is a network-based humanoid robot with 35 degrees of freedom, 6-DOFs for each arm and 4-DOFs for each hand. It also has two 6-DOFs legs and can reach the maximum walking speed of 0.9 Km/h.…”

Section: Overview Of the Resultsmentioning

confidence: 99%

“…Simon [27] in Figure 4j is an upper-torso humanoid robot with two degrees of freedom on the torso, two 7-DOFs arms and several degrees of freedom shared among the head, the neck, the ears and the eyes. (b) iCub [19] (c) Rollin' Justin [20] (d) NAO [21] (e) ABB FRIDA [22] (f) HRP-2 [23] (g) ROMEO [24] (h) HERB 2.0 [25] (i) MAHRU [26] (j) Simon [27] iCub [19] ( Figure 4b) was designed to have a high degree of manipulation. For this reason, each hand has 9 DOFs, and the arms have 7 DOFs.…”

Section: Overview Of the Resultsmentioning

confidence: 99%

Human-Like Arm Motion Generation: A Review

Gulletta¹,

Erlhagen²,

Bicho³

2020

Preprint

View full text Add to dashboard Cite

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analysed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioural and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

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“…The simulated humanoid robot model is MAHRU [17] which was developed by the Korean Institute of Science and Technology (Fig. 1).…”

Section: Simulation Resultsmentioning

confidence: 99%

“…If yes, the ZMP is switched at the next servo cycle. This can be computed using the following equation derived from (17). where T is the duration from the next servo time to half of the single support time.…”

Section: Lateral Motionmentioning

confidence: 99%

Velocity tracking algorithm in forward walking using estimated zmp by whole-body control framework

Lee

¹

,

Park

²

2013

2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids)

0

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This paper presents a forward walking strategy for humanoid robots using a whole-body control framework. Implementation of walking requires the coordination of movements between the feet and the center of mass (COM) of the system. In addition, the condition of preventing falling needs to be considered at the planning stage and later the robot is controlled to meet this condition upon execution. In this paper, assuming that the planned velocity of the COM and the corresponding foot trajectories are given, generating the desired COM position and velocity by estimating the ZMP of the foot is proposed to account for the stability condition. This strategy provides a way to implement walking without the explicit planning of the COM in the forward direction. The proposed approach is implemented and verified in a simulation of a humanoid robot.

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Network-based Humanoid ‘MAHRU’ as Ubiquitous Robotic Companion

Cited by 5 publications

References 14 publications

Human-Like Arm Motion Generation: A Review

Human-Like Arm Motion Generation: A Review

Human-Like Arm Motion Generation: A Review

Velocity tracking algorithm in forward walking using estimated zmp by whole-body control framework

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