Hardware and software architecture of the bimanual mobile manipulation robot HoLLiE and its actuated upper body

Hermann, A. M.; Sun, Jizhou; Xue, Zhixing; Ruehl, Steffen W.; Oberlaender, Jan; Roennau, Arne; Zoellner, J. Marius; Dillmann, Ruediger

doi:10.1109/aim.2013.6584106

Cited by 17 publications

(6 citation statements)

References 8 publications

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“…HoLLiE, Hermann et al (2013) is a mobile service robot with two functional arms and humanoid hands (see Figure 5). The robot was developed at the FZI Research Center for Information Technology for different tasks, such as accompanying visitors and mobile manipulation (see 1 ).…”

Section: Resultsmentioning

confidence: 99%

“…The target representation layer takes the target position and based on the relative distance to the base motion target point uses selective disinhibition to activate the correction primitives. We evaluated our approach with a humanoid robot, HoLLiE in Hermann et al (2013), by defining different targets on a plane and having the robot point to them (see Supplementary Video 1).…”

Section: Introductionmentioning

confidence: 99%

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Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives

et al. 2019

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The human motor system is robust, adaptive and very flexible. The underlying principles of human motion provide inspiration for robotics. Pointing at different targets is a common robotics task, where insights about human motion can be applied. Traditionally in robotics, when a motion is generated it has to be validated so that the robot configurations involved are appropriate. The human brain, in contrast, uses the motor cortex to generate new motions reusing and combining existing knowledge before executing the motion. We propose a method to generate and control pointing motions for a robot using a biological inspired architecture implemented with spiking neural networks. We outline a simplified model of the human motor cortex that generates motions using motor primitives. The network learns a base motor primitive for pointing at a target in the center, and four correction primitives to point at targets up, down, left and right from the base primitive, respectively. The primitives are combined to reach different targets. We evaluate the performance of the network with a humanoid robot pointing at different targets marked on a plane. The network was able to combine one, two or three motor primitives at the same time to control the robot in real-time to reach a specific target. We work on extending this work from pointing to a given target to performing a grasping or tool manipulation task. This has many applications for engineering and industry involving real robots.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives

et al. 2019

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“…A service architecture is proposed to solve the problem of heterogeneity in multi‐robot cooperation [9]. A mobile robot is able to perceive the surrounding environment and interact with people in [10]. However, function of cognitive and understanding object's intention are still not enough to meet humans' requirements.…”

Section: Introductionmentioning

confidence: 99%

Proposal of initiative service model for service robot

Hao

Cao

et al. 2017

CAAI Transactions on Intelligence Technology

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Service robots are becoming a part of today's life. To realise friendly human-robot interaction, an initiative service model for service robot is proposed, which is composed of three layers, i.e. information acquisition layer, in which communication information and environmental information are collected by sensors; decision layer, in which personal intention and emotional states are obtained by multi-modal emotion recognition and intention understanding, and users' demands are obtained by demand analysis model; initiative service execution layer, in which the task execution and emotion adaption of robot are carried out. Initiative service can sense motive of people, by which a humanised and real-time service could be realised. Drinking service experiments are performed, including passive service and initiative service of robots. Experimental results show that the drinking time of passive service lags behind the initiative service 30 min on average, and the initiative service renders drinking service 2 times more than passive service on average, besides, the water quantity provided by initiative service is more reasonable, which demonstrates the feasibility of the proposal. In prospect, initiative service model could be applied to many occasions in people's daily life, e.g. family service, caring for the elderly, and medical rehabilitation.

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“…The highly articulated mobile robots IMMP[11] (Industrial Mobile Manipulation Platform) and HoLLiE (House of Living Labs Intelligent Escort)[12] that plan their motions with the presented collision detection.…”

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confidence: 99%

Unified GPU voxel collision detection for mobile manipulation planning

Hermann

Drews

Bauer

et al. 2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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This paper gives an overview on our framework for efficient collision detection in robotic applications. It unifies different data structures and algorithms that are optimized for Graphics Processing Unit (GPU) architectures. A speed-up in various planning scenarios is achieved by utilizing storage structures that meet specific demands of typical use-cases like mobile platform planning or full body planning. The system is also able to monitor the execution of motion trajectories for intruding dynamic obstacles and triggers a replanning or stops the execution. The presented collision detection is deployed in local dynamic planning with live pointcloud data as well as in global a-priori planning. Three different mobile manipulation scenarios are used to evaluate the performance of our approach.

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Hardware and software architecture of the bimanual mobile manipulation robot HoLLiE and its actuated upper body

Cited by 17 publications

References 8 publications

Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives

Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives

Proposal of initiative service model for service robot

Unified GPU voxel collision detection for mobile manipulation planning

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