KUKA youBot - a mobile manipulator for research and education

Bischoff, Rainer; Huggenberger, Ulrich; Prassler, Erwin

doi:10.1109/icra.2011.5980575

Cited by 144 publications

(102 citation statements)

References 1 publication

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“…The omni-directional capability in Youbot [15] made it the best choice for the experiments because of space and size restrictions in the environment. As for the CPU, a computer running on Ubuntu in the Youbot is used.…”

Section: Methodsmentioning

confidence: 99%

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Experimental Investigation of Radio Signal Propagation in Scientific Facilities for Telerobotic Applications

Parasuraman

Kershaw

Ferré

2013

International Journal of Advanced Robotic Systems

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Understanding the radio signal transmission characteristics in the environment where the telerobotic application is sought is a key part of achieving a reliable wireless communication link between a telerobot and a control station. In this paper, wireless communication requirements and a case study of a typical telerobotic application in an underground facility at CERN are presented. Then, the theoretical and experimental characteristics of radio propagation are investigated with respect to time, distance, location and surrounding objects. Based on analysis of the experimental findings, we show how a commercial wireless system, such as Wi-Fi, can be made suitable for a case study application at CERN.

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Section: Methodsmentioning

confidence: 99%

“…is desirable that a reliable wireless video transmission system mounted on a small mobile robotic vehicle, such as the KUKA Youbot [15], is used to transmit the live camera feeds monitoring the industrial robots. In figure 1, the red portions indicate the area where this application is needed.…”

Section: Isolde Vision System For Remote Handlingmentioning

confidence: 99%

Experimental Investigation of Radio Signal Propagation in Scientific Facilities for Telerobotic Applications

Parasuraman

Kershaw

Ferré

2013

International Journal of Advanced Robotic Systems

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“…The experiments employed two Parrot AR.Drone 2.0 quadcopters (Krajník et al 2011) to perform the mission, and a KUKA Youbot (Bischoff et al 2011) robot to perform the role of intruder. In this way, the aerial robots were controlled by the mission operator and their information is available for the mission execution and analysis, whereas the ground robot was controlled by a person that was not involved in the mission and its information must be acquired by the aerial robots.…”

Section: Robots and Equipmentsmentioning

confidence: 99%

Analyzing and improving multi-robot missions by using process mining

et al. 2017

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Multi-robot missions can be compared to industrial processes or public services in terms of complexity, agents and interactions. Process mining is an emerging discipline that involves process modeling, analysis and improvement through the information collected by event logs. Currently, this discipline is successfully used to analyze several types of processes, but is hardly applied in the context of robotics. This work proposes a systematic protocol for the application of process mining to analyze and improve multi-robot missions. As an example, this protocol is applied to a scenario of fire surveillance and extinguishing with a fleet of UAVs. The results show the potential of process mining in the analysis of multi-robot missions and the detection of problems such as bottlenecks and inefficiencies. This work opens the way to an extensive use of these techniques in multi-robot missions, allowing the development of future systems for optimizing missions, allocating tasks to robots, detecting anomalies or supporting operator decisions.

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“…The application implements a framework for inferring and planning with respect to the movement of goal-oriented agents in an interactive multi-agent setupfull details can be found in Bordallo et al (2015). There are two types of agents navigating in the same physical space: autonomous robots represented by KUKA youBots (Bischoff et al 2011) and humans. Each agent is pursuing a goal (a specific spatial position in the scenario) while avoiding collisions with other agents, based on online sensor processing and beliefs concerning the latent goals of other agents.…”

Section: Introductionmentioning

confidence: 99%

Solving the task variant allocation problem in distributed robotics

et al. 2018

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We consider the problem of assigning software processes (or tasks) to hardware processors in distributed robotics environments. We introduce the notion of a task variant, which supports the adaptation of software to specific hardware configurations. Task variants facilitate the trade-off of functional quality versus the requisite capacity and type of target execution processors. We formalise the problem of assigning task variants to processors as a mathematical model that incorporates typical constraints found in robotics applications; the model is a constrained form of a multi-objective, multi-dimensional, multiple-choice knapsack problem. We propose and evaluate three different solution methods to the problem: constraint programming, a constructive greedy heuristic and a local search metaheuristic. Furthermore, we demonstrate the use of task variants in a real instance of a distributed interactive multi-agent navigation system, showing that our best solution method (constraint programming) improves the system's quality of service, as compared to the local search metaheuristic, the greedy heuristic and a randomised solution, by an average of 16, 31 and 56% respectively.

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KUKA youBot - a mobile manipulator for research and education

Cited by 144 publications

References 1 publication

Experimental Investigation of Radio Signal Propagation in Scientific Facilities for Telerobotic Applications

Experimental Investigation of Radio Signal Propagation in Scientific Facilities for Telerobotic Applications

Analyzing and improving multi-robot missions by using process mining

Solving the task variant allocation problem in distributed robotics

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