PDF-Discriminati raining of Kalman Filters Pieter Abbeel Adam Coates Michael Montemerlo Andre

Ho we er their perf ormance critically depends on lar ge number of modeling parameters which can be ery dif64257cult to obtain and ar often set via signi64257cant manual tweaking and at gr eat cost of engineering time In this paper we pr opose metho. upennedu Abstract Conditional random 57346elds for sequence label ing of fer adv antages er both generati mod els lik HMMs and classi57346ers applied at each sequence position Among sequence labeling tasks in language processing shallo parsing has re Our algorithm tunes the quality of its solution based on available search time at every step reusing previous search efforts When updated in formation regarding the underlying graph is received the algorithm incrementally repairs its previous solu t cmuedu Abstract In real world planning problems time for deliberation is often limited Anytime planners are well suited for these problems they 64257nd a feasi ble solution quickly and then continually work on improving it until time runs out In this cscmuedu thrun draft please do not circulate Abstract In the 1970s most research in robotics presupposed the ailability of xact models of robots and their en vironments Little emphasis as placed on sensing and the intrinsic limitations of modeling co The approach uses a fast implementation of scanmatching for mapping paired with a samplebased probabilistic method for localization Compact 3D maps are generated using a multiresolution approach adopted from the computer graphics literature fed by d umassedu Abstract ne spectral approach to alue function approxima tion has recently been proposed to automatically con struct basis functions from samples Global basis func tions called protov alue functions are generated by di agonalizing dif fusion Jin Kim Michael I ordan and Shankar Sastry Uni ersity of California Berk ele CA 94720 Abstract Autonomous helicopter 64258ight represents challenging control problem with comple x noisy dynamics In this paper we describe successful application of re stanfordedu Sebastian Thrun Computer Science Department Stanford University Stanford CA 94305 thrunaistanfordedu Michael Montemerlo Computer Science Department Stanford University Stanford CA 94305 mmdeaistanfordedu James Diebel Computer Science Depa The key innovation is a representation of the data association posterior in information form in which the proxim ity of objects and tracks are expressed by numerical links Updating these links requires linear time compared to exponential time requir E Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem Since that time due in large part to ad vances in digital computing the Kalman filter has been the subject of extensive re search and app Katz Son K Dao CS Di vision Uni ersity of California Berk ele ISL HRL Laboratories LLC Abstr act Mobile adhoc netw orking in olv es peer topeer communica tion in netw ork with dynamically changing topology Achie ving ener gy ef64257cient communicati stanfordedu Pieter Abbeel pabbeelcsstanfordedu Andrew Y Ng angcsstanfordedu Stanford University CS Department 353 Serra Mall Stanford CA 94305 USA Abstract We consider the problem of learning to follow a desired trajectory when given a small num ber Analysis . of. . the. . character. . of. . - . thickset. man, . ginger. . beard. , . ginger. . hair. , . bullish. neck. - . always. . talks. in . short. . sentences. , . from. time . to. time . looooooove. socks. Every time I . went out . with my mom I . asked her to . buy me all the cool . socks. I . kept adding them to my collection. Since my mom saw that I loved . socks, . one day she asked me if .