Continual Adaptation of Semantic Segmentation using Complementary 2D-3D Data Representations

Semantic segmentation networks are usually pre-trained once and not updated during deployment. As a consequence, misclassifications commonly occur if the distribution of the training data deviates from the one encountered during the robot's operation. We propose to mitigate this problem by adapting the neural network to the robot's environment during deployment, without any need for external supervision. Leveraging complementary data representations, we generate a supervision signal, by probabilistically accumulating consecutive 2D semantic predictions in a volumetric 3D map. We then train the network on renderings of the accumulated semantic map, effectively resolving ambiguities and enforcing multi-view consistency through the 3D representation. In contrast to scene adaptation methods, we aim to retain the previously-learned knowledge, and therefore employ a continual learning experience replay strategy to adapt the network. Through extensive experimental evaluation, we show successful adaptation to real-world indoor scenes both on the ScanNet dataset and on in-house data recorded with an RGB-D sensor. Our method increases the segmentation accuracy on average by 9.9% compared to the fixed pre-trained neural network, while retaining knowledge from the pre-training dataset.Comment: Accepted for IEEE Robotics and Automation Letters (R-AL 2022

Leadership for Organisational Adaptability: How Enabling Leaders Create Adaptive Space

Organisational adaptability is the ability of an organisation to recognise the need to change and seize opportunities in dynamic environments. In an increasingly complex world, leadership must pay attention to dynamic, distributed, and contextual aspects in order to position their organisations for adaptability. The theory of dynamic capabilities constitutes a central concept for the requirements that enable organisational adaptability. Recent research suggested a model of “leadership for organisational adaptability” embedded in the theory of dynamic capabilities and ambidextrous leadership. This model ascribes leaders the task of creating “adaptive spaces”, which are ways to engage in tension that arises when new ideas collide with an organisation’s operational system, in order to generate and scale innovation. This work employs a qualitative research design by conducting expert interviews with participants from the management consulting industry as an exemplary object of research, and it identifies ways by which leaders can create such adaptive spaces. Findings indicate that leaders predominantly achieve this by providing employees with head space and opportunities to connect with others and promote diversity within their organisations. However, they could engage more actively in activities that pressure the organisation to change, leverage network structures to scale innovation, and in developing employees. It further emerged that organisations have not fully internalised the notion of distributed leadership, which is deemed crucial for coping with complexity.TU Berlin, Open-Access-Mittel – 202

Prospectus, October 22, 2008

https://spark.parkland.edu/prospectus_2008/1022/thumbnail.jp

Was kennzeichnet gute Wohlfahrtsstaatlichkeit? Normative Traditionen des Wohlfahrtsstaatsdenkens in Deutschland: Bericht zu den 9. Heppenheimer Tagen zur christlichen Gesellschaftsethik

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Wohlfahrtsverbände im Modernisierungsstress – Geschichte, Gegenwart und Zukunft der Freien Wohlfahrtspflege. Bericht zu den 6. Heppenheimer Tagen zur christlichen Gesellschaftsethik

Bericht zu den 6. Heppenheimer Tagen zur christlichen Gesellschaftsethi

Die Wohnungsfrage – eine Gerechtigkeitsfrage: Bericht zu den 10. Heppenheimer Tagen zur christlichen Gesellschaftsethik

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