{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T05:10:35Z","timestamp":1698297035714},"reference-count":13,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2006,10,31]],"date-time":"2006-10-31T00:00:00Z","timestamp":1162252800000},"content-version":"vor","delay-in-days":4961,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Visual. Comput. Animat."],"published-print":{"date-parts":[[1993,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Programming the motions of an autonomous planetary robot moving in an hostile and hazardous environment is a complex task which requires both the construction of nominal motion plans and the anticipation as far as possible of the effects of the interactions existing between the vehicle and the terrain. In this paper we show how physical models and dynamic simulation tools can be used for amending and completing a nominal motion plan provided by a classical geometrical path planner. The purpose of our physical modeller\u2010simulator is to anticipate the dynamic behaviour of the vehicle while executing the nominal motion plan. Then the obtained simulation results can be used to assess and optimize the nominal motion plan. In the first part, we outline the physical models that have been used for modelling the different types of vehicle, of terrain and of vehicle\u2010surface interactions. Then we formulate the motion planning problem through the definition of two basic abstract constructions derived from physical model: the concept of generalized obstacle and the concept of physical target. We show with various examples how it is possible, when using this method, to solve the locomotion problem and the obstacle avoidance problem simultaneously and, furthermore, to provide the human operator with a true force feedback gestural control over the simulated robot.<\/jats:p>","DOI":"10.1002\/vis.4340040204","type":"journal-article","created":{"date-parts":[[2006,11,17]],"date-time":"2006-11-17T14:32:07Z","timestamp":1163773927000},"page":"79-94","source":"Crossref","is-referenced-by-count":2,"title":["Physical simulation of land vehicles with obstacle avoidance and various terrain interactions"],"prefix":"10.1002","volume":"4","author":[{"given":"St\u00e9phane","family":"Jimenez","sequence":"first","affiliation":[]},{"given":"Annie","family":"Luciani","sequence":"additional","affiliation":[]},{"given":"Olivier","family":"Raoult","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2006,10,31]]},"reference":[{"issue":"2","key":"e_1_2_1_2_2","first-page":"77","article-title":"On non honolomic mobile robots and optimal maneuvring","volume":"3","author":"Barraquant J.","year":"1989","journal-title":"Revue d'intelligence artificielle"},{"key":"e_1_2_1_3_2","unstructured":"T.Fraichard C.LaugierandG.Lievin \u2018Robot motion planning: the case of non\u2010holonomic mobiles in a dynamic world\u2019 IROS'90 Tsuchiura July1990."},{"key":"e_1_2_1_4_2","unstructured":"J.Barraquant B.LangloisandJ. 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