Refine
H-BRS Bibliography
- yes (212) (remove)
Departments, institutes and facilities
- Fachbereich Informatik (62)
- Fachbereich Wirtschaftswissenschaften (61)
- Institut für Technik, Ressourcenschonung und Energieeffizienz (TREE) (39)
- Fachbereich Angewandte Naturwissenschaften (35)
- Fachbereich Ingenieurwissenschaften und Kommunikation (33)
- Institut für Verbraucherinformatik (IVI) (15)
- Institute of Visual Computing (IVC) (15)
- Fachbereich Sozialpolitik und Soziale Sicherung (14)
- Institut für Cyber Security & Privacy (ICSP) (9)
- Institut für funktionale Gen-Analytik (IFGA) (6)
Document Type
- Conference Object (79)
- Article (71)
- Part of a Book (23)
- Book (monograph, edited volume) (17)
- Contribution to a Periodical (7)
- Report (7)
- Conference Proceedings (2)
- Doctoral Thesis (2)
- Bachelor Thesis (1)
- Research Data (1)
Year of publication
- 2016 (212) (remove)
Has Fulltext
- no (212) (remove)
Keywords
- Lehrbuch (6)
- Betriebswirtschaftslehre (2)
- Corporate Social Responsibility (2)
- Dielectric analysis (2)
- E-Business (2)
- Fas (2)
- Intelligent Transport System (2)
- Kommunikation (2)
- Large, high-resolution displays (2)
- Lignin (2)
Results from the EU-project iStoppFalls : feasibility, effectiveness, approach for fall prevention
(2016)
Autonomous mobile robots comprise of several hardware and software components. These components interact with each other continuously in order to achieve autonomity. Due to the complexity of such a task, a monumental responsibility is bestowed upon the developer to make sure that the robot is always operable. Hence, some means of detecting faults should be readily available. In this work, the aforementioned fault-detection system is a robotic black box (RBB) attached to the robot which acquires all the relevant measurements of the system that are needed to achieve a fault-free robot. Due to limited computational and memory resources on-board the RBB, a distributed diagnosis is proposed. That is, the fault diagnosis task (detection and isolation) is shared among an on-board component (the black box) and an off-board component (an external computer). The distribution of the diagnosis task allows for a non-intrusive method of detecting and diagnosing faults, in addition to the ability of remotely diagnosing a robot and potentially issuing a repair command. In addition to decomposing the diagnosis task and allowing remote diagnosability of the robot, another key feature of this work is the addition of expert human knowledge to aid in the fault detection process.
Domestic Robotics
(2016)