We present a general approach to planning with incomplete information in\nAnswer Set Programming (ASP). More precisely, we consider the problems of\nconformant and conditional planning with sensing actions and assumptions. We\nrepresent planning problems using a simple formalism where logic programs\ndescribe the transition function between states, the initial states and the\ngoal states. For solving planning problems, we use Quantified Answer Set\nProgramming (QASP), an extension of ASP with existential and universal\nquantifiers over atoms that is analogous to Quantified Boolean Formulas (QBFs).\nWe define the language of quantified logic programs and use it to represent the\nsolutions to different variants of conformant and conditional planning. On the\npractical side, we present a translation-based QASP solver that converts\nquantified logic programs into QBFs and then executes a QBF solver, and we\nevaluate experimentally the approach on conformant and conditional planning\nbenchmarks. Under consideration for acceptance in TPLP.\n