Wyniki przedstawione w niniejszej rozprawie mog¡ by¢ podstaw¡ do dalszych bada«. Niektóre z zaprezentowanych metod mo»na ulepszy¢, cz¦±¢ z nich mo»na te» rozwin¡¢ b¡d¹ wykorzysta¢ jako elementy skªadowe dla nowych, bardziej skomplikowanych metod.
Poni»ej przedstawiono proponowane kierunki rozwoju metod zaprezento-wanych w rozprawie.
• Rozbudowa metody kalibracji poªo»enia sensorów w ukªadzie robota o elementy autonomii: samodzielne znajdowanie pªaskich powierzchni oraz wykrywanie potrzeby ponownej kalibracji ukªadu.
• Wzbogacenie metod budowy mapy o sposoby uzupeªniania pustych przestrzeni.
• Dalsza wery kacja mo»liwo±ci planowania ruchu robota krocz¡cego przy u»yciu map zbudowanych przedstawionymi metodami.
• Wyznaczenie modeli niepewno±ci dla innych sensorów zwracaj¡cych g¦-st¡ map¦ gª¦bi (kamery TOF, skanery 3D) oraz wery kacja zastosowa-nia przedstawionych metod z tymi sensorami.
• Wery kacja wykorzystania innych metod optymalizacji (takich jak Par-ticle Swarm Optimization lub algorytmy genetyczne) w samolokalizacji na podstawie map wysoko±ci.
• Implementacja kompletnej metody SLAM dedykowanej robotom kro-cz¡cym na podstawie przedstawionych algorytmów mapowania i samo-lokalizacji.
• Rozwini¦cie metod budowy mapy tak, aby umo»liwiaªy modelowanie du»ych obszarów.
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