An autonomous guided vehicle includes a frame, a drive section, a payload handler, a sensor system, and a supplemental sensor system. The sensor system has electro-magnetic sensors, each responsive to interaction or interface of a sensor emitted or generated electro-magnetic beam or field with a physical characteristic, the electro-magnetic beam or field being disturbed by interaction or interface with the physical characteristic, and which disturbance is detected by and effects sensing of the physical characteristic. The sensor system generates sensor data embodying at least one of a vehicle navigation pose or location information and payload pose or location information. The supplemental sensor system supplements the sensor system, and is, at least in part, a vision system with cameras disposed to capture image data informing the at least one of a vehicle navigation pose or location and payload pose or location supplement to the information of the sensor system.

Visual-inertial tracking of an eyewear device using a rolling shutter camera(s). The eyewear device includes a position determining system. Visual-inertial tracking is implemented by sensing motion of the eyewear device. An initial pose is obtained for a rolling shutter camera and an image of an environment is captured. The image includes feature points captured at a particular capture time. A number of poses for the rolling shutter camera is computed based on the initial pose and sensed movement of the device. The number of computed poses is responsive to the sensed movement of the mobile device. A computed pose is selected for each feature point in the image by matching the particular capture time for the feature point to the particular computed time for the computed pose. The position of the mobile device is determined within the environment using the feature points and the selected computed poses for the feature points.

Disclosed herein are a method of localization by synchronizing multi sensors and a robot implementing the same. The robot according to an embodiment includes a controller that, when a first sensor acquires first type information, generates first type odometry information using the first type information, that, at a time point when the first type odometry information is generated, acquires second type information by controlling a second sensor and then generates second type odometry information using the second type information, and that the robot by combining the first type odometry information and the second type odometry information.

A control device includes a storage device which has stored a program, and a hardware processor, in which the hardware processor executes the program stored in the storage device, thereby acquiring a peripheral image of the mobile object, which is an image captured by a fisheye camera mounted on a mobile object, calculating an instruction regarding future traveling of the mobile object as a base trajectory in an orthogonal coordinate system, coordinate-converting the acquired base trajectory in the orthogonal coordinate system into a base trajectory in a fisheye camera coordinate system, calculating a risk of the base trajectory in the fisheye camera coordinate system on the basis of the peripheral image, and the base trajectory in the fisheye camera coordinate system, and calculating a traveling trajectory by modifying the base trajectory in the orthogonal coordinate system on the basis of the risk of the base trajectory in the fisheye camera coordinate system.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

This disclosure relates generally to systems and methods for object detection using a geometric semantic map based robot navigation using an architecture to empower a robot to navigate an indoor environment with logical decision making at each intermediate stage. The decision making is further enhanced by knowledge on actuation capability of the robots and that of scenes, objects and their relations maintained in an ontological form. The robot navigates based on a Geometric Semantic map which is a relational combination of geometric and semantic map. In comparison to traditional approaches, the robot's primary task here is not to map the environment, but to reach a target object. Thus, a goal given to the robot is to find an object in an unknown environment with no navigational map and only egocentric RGB camera perception.

An autonomous robotic exploration method based on a reduced approximated generalized Voronoi graph, the method including: 1) constructing a reduced approximated generalized Voronoi topological map based on a morphological method; 2) obtaining an Next-Best-View and planning a global path from the robot to the Next-Best-View; and 3) navigating to the Next-Best-View along the global path R={r.sub.0, r.sub.1, r.sub.2, . . . , p.sub.NBV} based on a visual force field (VFF) algorithm.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

The present disclosure provides a mobile robot. The mobile robot includes a body, a pair of spin mops rotatably mounted to the body, a mop motor configured to provide a driving force to the pair of spin mops, an optical flow sensor configured to obtain bottom-view image information using light at a regular time interval, and a controller configured to determine whether the material of the floor is a troublesome material based on the bottom-view image information sensed by the optical flow sensor and to control, upon determining that the material of the floor is a troublesome material, the mop motor to perform an entry restriction operation.

Vision systems for autonomous machines and methods of using same during machine localization are provided. Exemplary systems and methods may reduce computing resources needed to perform vision-based localization by selecting the most appropriate camera from two or more cameras, and optionally selecting only a portion of the selected camera's field of view, from which to perform vision-based location correction. Other embodiments may provide camera lens coverings that maintain optical clarity while operating within debris-filled environments.