Turn-by-turn navigation

About: Turn-by-turn navigation is a research topic. Over the lifetime, 2243 publications have been published within this topic receiving 52838 citations.

Adjustable destination icon in a map navigation tool

Abstract: A map navigation tool presents directions using a map navigation user interface that simplifies navigation in various ways. In particular, the map navigation tool uses a destination icon that directs the user towards an end location of a route when the user is close to the end location. For example, the map navigation tool obtains multiple list items of a list of directions. Based at least in part on current location, the tool determines that a destination icon is to be displayed. For example, the tool checks whether the current location is within a threshold distance from or past the end location. The tool then renders the destination icon, which indicates direction towards the end location. The tool can further adjust the destination icon depending on current location, for example, rotating the destination icon or switching between multiple destination icons representing left, right, ahead and behind directions.

Semi-autonomous robot that supports multiple modes of navigation

Abstract: Described herein are technologies pertaining to robot navigation. The robot includes a video camera that is configured to transmit a live video feed to a remotely located computing device. A user interacts with the live video feed, and the robot navigates in its environment based upon the user interaction. In a first navigation mode, the user selects a location, and the robot autonomously navigates to the selected location. In a second navigation mode, the user causes the point of view of the video camera on the robot to change, and thereafter causes the robot to semi-autonomously drive in a direction corresponding to the new point of view of the video camera. In a third navigation mode, the user causes the robot to navigate to a selected location in the live video feed.

Techniques for analyzing the performance of websites

Abstract: In one embodiment, a method of analyzing a performance of locations on a computer network included the steps of collecting navigation histories of client computers (110) on the computer network, processing the navigation histories to obtain relevant navigation data (502, 506), and generating a report in accordance with user provided criteria (510, 516, 526), the report being based on the relevant navigation data and indicative of a performance of a location on the computer network. The computer network may include the Internet and the locations may compromise websites.

A New Visualization Concept for Navigation Systems

Abstract: At present, various types of car navigation systems are progressively entering the market. Simultaneously, mobile outdoor navigation systems for pedestrians and electronic tourist guides are already available on handheld computers. Although, the depiction of the geographical information on these appliances has increasingly improved during the past years, users are still handicapped having to interpret an abstract metaphor on the navigation display and translate it to their real world.

User experiences with activity-based navigation on mobile devices

Abstract: We introduce activity-based navigation, which uses human activities derived from sensor data to help people navigate, in particular to retrace a "trail" previously taken by that person or another person. Such trails may include step counts, walking up/down stairs or taking elevators, compass directions, and photos taken along a user's path, in addition to absolute positioning (GPS and maps) when available. To explore the user experience of activity-based navigation, we built Greenfield, a mobile device interface for finding a car. We conducted a ten participant user study comparing users' ability to find cars across three different presentations of activity-based information as well as verbal instructions. Our results show that activity-based navigation can be used for car finding and suggest its promise more generally for supporting navigation tasks. We present lessons for future activity-based navigation interfaces, and motivate further work in this space, particularly in the area of robust activity inference.