Transition Cells and Neural Fields for Navigation and Planning Export

@incollection{citeulike:2910641, abstract = {We have developped a mobile robot control system based on hippocampus and prefrontal models. We propose an alternative to models that rely on cognitive maps linking place cells. Our experiments show that using transition cells is more efficient than using place cells. The transition cell links two locations with the integrated direction used. Furthermore, it is possible to fuse the different directions proposed by nearby transitions and obstacles into an effective direction by using a Neural Field. The direction to follow is the stable fixed point of the Neural Field dynamics, and its derivative gives the angular rotation speed. Simulations and robotics experiments are carried out.}, author = {Cuperlier, Nicolas and Quoy, Mathias and Laroque, Philippe and Gaussier, Philippe}, citeulike-article-id = {2910641}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/11499220_36}, doi = {10.1007/11499220_36}, journal = {Mechanisms, Symbols, and Models Underlying Cognition}, keywords = {biological-inspired-modeling, cell-models, cog-neuro, comparative-neuro, evolution-of-intelligence, neuro-coding, neuro-computation, neuro-morphic, neuro-spike, robotics, spatial-cognition}, pages = {346--355}, posted-at = {2008-06-20 16:18:49}, priority = {2}, title = {Transition Cells and Neural Fields for Navigation and Planning}, url = {http://dx.doi.org/10.1007/11499220_36}, year = {2005} }

TY - CHAP ID - citeulike:2910641 L3 - citeulike-article-id:2910641 N2 - We have developped a mobile robot control system based on hippocampus and prefrontal models. We propose an alternative to models that rely on cognitive maps linking place cells. Our experiments show that using transition cells is more efficient than using place cells. The transition cell links two locations with the integrated direction used. Furthermore, it is possible to fuse the different directions proposed by nearby transitions and obstacles into an effective direction by using a Neural Field. The direction to follow is the stable fixed point of the Neural Field dynamics, and its derivative gives the angular rotation speed. Simulations and robotics experiments are carried out. JF - Mechanisms, Symbols, and Models Underlying Cognition EP - 355 TI - Transition Cells and Neural Fields for Navigation and Planning SP - 346 KW - biological-inspired-modeling KW - cell-models KW - cog-neuro KW - comparative-neuro KW - evolution-of-intelligence KW - neuro-coding KW - neuro-computation KW - neuro-morphic KW - neuro-spike KW - robotics KW - spatial-cognition AU - Cuperlier, Nicolas AU - Quoy, Mathias AU - Laroque, Philippe AU - Gaussier, Philippe PY - 2005/// UR - http://dx.doi.org/10.1007/11499220_36 ER -