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- Gao, Robert X., et al.
(författare)
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Human motion recognition and prediction for robot control
- 2021
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Ingår i: Advanced Human-Robot Collaboration in Manufacturing. - Cham : Springer Nature. ; , s. 261-282
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The ever-increasing demand for higher productivity, lower cost and improved safety continues to drive the advancement of manufacturing technologies. As one of the key elements, human-robot collaboration (HRC) envisions a workspace where humans and robots can dynamically collaborate for improved operational efficiency while maintaining safety. As the effectiveness of HRC is affected by a robot's ability to sense, understand and forecast the state of the collaborating human worker, human action recognition and motion trajectory prediction have become a crucial part in realising HRC. In this chapter, deep-learning-based methods for accomplishing this goal, based on the in-situ sensing data from the workspace are presented. Specifically, to account for the variability and heterogeneity of human workers during assembly, a context-aware deep convolutional neural network (DCNN) has been developed to identify the task-associated context for inferencing human actions. To improve the accuracy and reliability of human motion trajectory prediction, a functional unit-incorporated recurrent neural network (RNN) has been developed to parse worker's motion patterns and forecast worker's future motion trajectories. Collectively, these techniques allow the robot to answer the question: "which tool or part should be delivered to which location next?", and enable online robot action planning and execution for the collaborative assembly operation. The methods developed are experimentally evaluated, with the collaborative assembly of an automotive engine as a case study.
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| 4. |
- Mathew, Aji P., 1971-, et al.
(författare)
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Nanocellulose based membranes for water purification : Fundamental concepts and Scale-up potential
- 2018
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Ingår i: Nanocellulose and Sustainability. - : CRC Press. - 9781498761031 - 9781351262910 ; , s. 129-146
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Bokkapitel (refereegranskat)abstract
- Nanocellulose, which offers a combination of biosorption, nanodimension and unique cellulosic nature, has a potential for a new and green route to solve the water pollution problems. The chapter focuses on water purification via adsorption process using nanocellulose and its membranes. The mechanism of purification is based on the capability of the nanocellulose and/or nanochitin to selectively adsorb, store and desorb contaminants from industrial water and drinking water while passing through a nanoporous, ultraporous or semi-permeable membrane. Membranes may be classified according to characteristic pore size. Layered membranes are developed as an attempt to increase the membrane flux while providing easy accessibility to functional groups on the nanocellulose. The electrospun fibrous membranes have also shown potential as an excellent support layer for a secondary active surface by creating a more complete secondary layer of a bilayered composite membrane. The design of an efficient and economical module with high surface area is crucial for successful commercialisation of membrane processes.
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| 5. |
- Mathew, Aji P., et al.
(författare)
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Nanocellulose for water purification membranes
- 2013
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Ingår i: Production and Applications of Cellulose Nanomaterials. - : TAPPI Press. - 9781595102249 ; , s. 155-156
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Bokkapitel (refereegranskat)abstract
- Nanocelluloses have demonstrated good adsorption capacity towards dyes, heavy metal ions, pesticides etc. and combined with their good mechanical strength, high surface area, crystallinity and moisture stability are expected to be a promising functional entity in the next generation of nano-enabled membranes. Furthermore, the large number of functional groups present on the surface of these membranes gives a positive approach to modify the surface according to our needs, thus increasing the selectivity of pollutants. When used in combination with biopolymers/ biodegradable polymers can lead to fully biobased water purification membranes.
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