An electronic apparatus comprising: a storage configured to store at least one instruction; at least one sensor; and at least one processor configured to execute the at least one instruction to: while the electronic apparatus is moving, capture a surrounding image and obtain location information by using the at least one sensor, when an unable-to-move situation occurs while the electronic apparatus is moving, generate context data for training one or more data recognition models, the context data comprising: a surrounding image, captured within a predetermined time before a time when the unable-to-move situation has occurred, and location information, corresponding to a time when the surrounding image is captured, store, in the storage, the generated context data corresponding to the unable-to-move situation having occurred, and train the one or more data recognition models to learn a criterion for the unable-to-move situation by using, as a training data, the generated context data corresponding to the unable-to-move situation having occurred, wherein the at least one processor is further configured to: determine, using the trained one or more data recognition models, whether or not a subsequent surrounding image and subsequent location information obtained while the electronic apparatus is moving match the context data stored in the storage, and when the subsequent surrounding image and the subsequent location information obtained while the electronic apparatus is moving match the context data, estimate, that the unable-to-move situation corresponding to the matched context data is going to occur; and control to avoid the estimated unable-to-move situation. a storage configured to store at least one instruction; at least one sensor; and at least one processor configured to execute the at least one instruction to: while the electronic apparatus is moving, capture a surrounding image and obtain location information by using the at least one sensor, when an unable-to-move situation occurs while the electronic apparatus is moving, generate context data for training one or more data recognition models, the context data comprising: a surrounding image, captured within a predetermined time before a time when the unable-to-move situation has occurred, and location information, corresponding to a time when the surrounding image is captured, store, in the storage, the generated context data corresponding to the unable-to-move situation having occurred, and train the one or more data recognition models to learn a criterion for the unable-to-move situation by using, as a training data, the generated context data corresponding to the unable-to-move situation having occurred, wherein the at least one processor is further configured to: determine, using the trained one or more data recognition models, whether or not a subsequent surrounding image and subsequent location information obtained while the electronic apparatus is moving match the context data stored in the storage, and when the subsequent surrounding image and the subsequent location information obtained while the electronic apparatus is moving match the context data, estimate, that the unable-to-move situation corresponding to the matched context data is going to occur; and control to avoid the estimated unable-to-move situation. while the electronic apparatus is moving, capture a surrounding image and obtain location information by using the at least one sensor, when an unable-to-move situation occurs while the electronic apparatus is moving, generate context data for training one or more data recognition models, the context data comprising: a surrounding image, captured within a predetermined time before a time when the unable-to-move situation has occurred, and location information, corresponding to a time when the surrounding image is captured, a surrounding image, captured within a predetermined time before a time when the unable-to-move situation has occurred, and location information, corresponding to a time when the surrounding image is captured, store, in the storage, the generated context data corresponding to the unable-to-move situation having occurred, and train the one or more data recognition models to learn a criterion for the unable-to-move situation by using, as a training data, the generated context data corresponding to the unable-to-move situation having occurred, wherein the at least one processor is further configured to: determine, using the trained one or more data recognition models, whether or not a subsequent surrounding image and subsequent location information obtained while the electronic apparatus is moving match the context data stored in the storage, and when the subsequent surrounding image and the subsequent location information obtained while the electronic apparatus is moving match the context data, estimate, that the unable-to-move situation corresponding to the matched context data is going to occur; and control to avoid the estimated unable-to-move situation. determine, using the trained one or more data recognition models, whether or not a subsequent surrounding image and subsequent location information obtained while the electronic apparatus is moving match the context data stored in the storage, and when the subsequent surrounding image and the subsequent location information obtained while the electronic apparatus is moving match the context data, estimate, that the unable-to-move situation corresponding to the matched context data is going to occur; and control to avoid the estimated unable-to-move situation.