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The State of Lifelong Learning in Service Robots: Current Bottlenecks in Object Perception and Manipulation by Kasaei, S. Hamidreza; Melsen, Jorik; van Beers, Floris; Steenkist, Christiaan; Voncina, Klemen is a scholarly article available to read on EtoBox.

What is The State of Lifelong Learning in Service Robots: Current Bottlenecks in Object Perception and Manipulation about?

Service robots are appearing more and more in our daily life. The development of service robots combines multiple fields of research, from object perception to object manipulation. The state-of-the-art continues to improve to make a proper coupling between object perception and manipulation. This coupling is necessary for service robots not only to perform various tasks in a reasonable amount of time but also to continually adapt to new environments and safely interact with non-expert human users. Nowadays, robots are able to recognize various objects, and quickly plan a collision-free trajectory to grasp a target object in predefined settings. Besides, in most of the cases, there is a reliance on large amounts of training data. Therefore, the knowledge of such robots is fixed after the training phase, and any changes in the environment require complicated, time-consuming, and expensive robot re-programming by human experts. Therefore, these approaches are still too rigid for real-life applications in unstructured environments, where a significant portion of the environment is unknown and cannot be directly sensed or controlled. In such environments, no matter how extensive the tra

Author

Kasaei, S. Hamidreza; Melsen, Jorik; van Beers, Floris; Steenkist, Christiaan; Voncina, Klemen

Published

2020

Language

EN