Distributed control for an anthropomimetic robot

Jantsch, Michael; Wittmeier, Steffen; Knoll, Alois

doi:10.1109/iros.2010.5651169

Cited by 19 publications

(15 citation statements)

References 8 publications

(10 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…All muscle units are controlled by distributed, custom-built Electronic Control Units (ECUs) which are interfaced via a Controller Area Network (CAN) [14], [1]. Each ECU is capable of controlling two muscle units and is equipped with a microcontroller, a CAN interface, motor drivers for two brushed DC motors, several Analog/Digital (A/D) converters for analog sensor connection and two integrated Hall-effectbased measurement devices in the motor loop for motor current feedback (see also subsection II-C).…”

Section: Resultsmentioning

confidence: 99%

Anthrob - A printed anthropomimetic robot

Jantsch

Wittmeier²,

Dalamagkidis³

et al. 2013

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

Self Cite

View full text Add to dashboard Cite

Abstract-Anthropomimetic robotics differ from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones and joints [1]. Prominent examples for this class of robots are the robots developed at the JSK laboratory of the University of Tokyo and the robots developed by the EU-funded project Embodied Cognition in a Compliantly Engineered Robot (Eccerobot). However, the high complexity of these robots as well as their lack of sensors has so far failed to provide the desired new insights in the field of control.Therefore, we developed the simplified but sensorized robot Anthrob. The robot replicates the human upper limb and features 13 compliant tendon driven uni-and biarticular muscles as well as a spherical shoulder joint. Whenever possible, Selective Laser Sintering (SLS) was used for the production of the robot parts to reduce the production costs and to implement cutting-edge technologies, such as tendon canals or solid-state joints.

show abstract

Section: Resultsmentioning

confidence: 99%

Anthrob - A printed anthropomimetic robot

Jantsch

Wittmeier²,

Dalamagkidis³

et al. 2013

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

Self Cite

View full text Add to dashboard Cite

show abstract

“…Furthermore it allows for a detailed simulation of the muscular system, including a refined version of the motor dynamics specified in Section III-B, additionally featuring Coulomb friction. Furthermore, not only the robot itself but also the control architecture as described in [2] is modeled, so the force control loops are executed asynchronously both to the simulation and the high-level control, as they would in a distributed system [11].…”

Section: Resultsmentioning

confidence: 99%

“…In this work we would like to propose a whole body control strategy for an anthropomimetic robot [1], based on the hierarchical control architecture described in [2]. Anthropomimetic robots are highly bio-inspired and mimic not only the general appearance of the human body, but also the mechanisms of the musculoskeletal system, like bones, joints, and muscles.…”

Section: Introductionmentioning

confidence: 99%

A scalable joint-space controller for musculoskeletal robots with spherical joints

Jantsch

Schmaler

Wittmeier

et al. 2011

2011 IEEE International Conference on Robotics and Biomimetics

Self Cite

View full text Add to dashboard Cite

Abstract-In the long history of robotics research, the most prominent problem has always been, to develop robots that can safely operate in human-centered environments. One way towards the goal of a safe, and human-friendly robot, is to incorporate more and more of the flexibility that can be found in humans, by mimicking the internal mechanisms. In this work we propose a scalable joint-space control scheme based on computed torque control for an anthropomimetic robot. To achieve this, the dynamic system model of the robot is decomposed into hierarchical subsystems, using scalable modeling algorithms where possible. Machine learning techniques were employed to tackle the problem of muscle force to joint torque mapping.The developed control scheme has been evaluated using the highly refined simulation of an anthropomimetic robot arm featuring 11 muscles, a revolute elbow joint and a spherical shoulder joint. We show trajectory tracking based on a lowlevel muscle and a high-level joint control scheme, taking into account the coupling between the joints due to inertial reactions and bi-articular muscles.

show abstract

“…Current sensors have been included in the ECUs of the real robot to measure the magnitude of the current drawn by the DC motor [17]. This sensor has been also included in the simulation by providing the required interfaces to access the current i of the DC motor model (see also Section V-A).…”

Section: Current Sensor Modelmentioning

confidence: 99%

“…A distributed, bio-inspired control architecture has been implemented for the ECCEROBOTS [17]. In this architecture, the individual muscles are controlled by dedicated ECUs with a control loop frequency of 500 Hz.…”

Section: Muscle Controlmentioning

confidence: 99%