Objective
The proposed research is directed at developing advanced neural schemes for obj ect-oriented, adaptive, reaching, grasping and manipulation in robotics, with i ncreased stability and robustness. They will be oriented to robotic service app lications, and especially for helping people with motor disabilities. The scien tific objectives of the project are: - Transfer of fundamental biological princ iples from cognitive-motor behaviour to antropomorphic robotics. - Construction of a high level, hardware independent, adaptive and modular library of element ary hand gestures. - New neural schemes that mimic the known cooperation betwee n cerebral cortex and cerebellum/basal ganglia during cognitive motor behaviour in manipulation. - Specifications for a subsequent industrial research project to be carried out by the endorsers The technical objectives of the project ar e: - Biological neural networks capable of construct grasp plans in the face of both functional and objectspecific constraints. - A language of opposition spa ce and virtual finger, oriented to construct a sequence learning of self adapti ve elementary hand gestures with total independence of application and environm ent. - Adaptive neural controllers wich, tested within laboratory environment u sing computer simulation, will be capable of generalising their skills in the s caling-up process to different robotics hands. The present project will transfe r human planning processes to robotics, while incorporating experimental result s from behavioural, anatomical, and neurophysiological studies. A well-defined robust set of mathematical models, elementary library of gestures, behavioural modules, and a selection mechanism over them will produce a considerable improv ement in the building of flexible and robust control systems for robot hands. M oreover, it will imply a reduction of the time and efforts necessary in the sca ling-up from laboratory to service robotics and a reduction of danger where rob ots must interact with humans. The generic neural models for human-like, flexib le, adaptive manipulation are not limited to the robotic service industry. The results of the present project are applicable in the whole area of manufacturin g where compliance is desirable to interact with the changing environment.
Fields of science
Not validated
Not validated
- natural sciencesbiological sciencesneurobiology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcontrol systems
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
- natural sciencesmathematicsapplied mathematicsmathematical model
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Call for proposal
Data not availableFunding Scheme
CSC - Cost-sharing contractsCoordinator
47151 Valladolid
Spain