Method for an autonomous cleaning apparatus, the method comprising the steps of: scanning a vicinity of an autonomous cleaning apparatus by means of at least one sensor; detecting an unreachable area, being unreachable by the autonomous cleaning apparatus; detecting a door in proximity to the unreachable area; detecting that the unreachable area is unreachable due to the positioning of the door wing; automatically moving the door wing, by the autonomous cleaning apparatus, in order to obtain access to and clean the unreachable area.

A determination device includes: route detection circuitry which detects, a first continuous body as a first part of a one or more first direction distance information with respect to a first object, and a second continuous body as a second part of the one or more first direction distance information with respect to a second object, in a first direction along a first route on which the moving body moves, and a third continuous body as the second part, in a second direction; route determination circuitry which determines presence or absence of a second route along the third continuous body.

A system and method is provided for delivering electric energy to an electric vehicle via electric charging stations or kiosks where an energy delivery point is configured to provide energy to the electric vehicle via a connector or a wireless energy source. The method involves charging an electric vehicle by detecting, using a RFID tag reader associated with an electric vehicle, signals emanating from a marker positioned on the ground, where the marker includes one or more RFID tags, and where the RFID tag reader is able to recognize the signals despite weather conditions where the ground is covered by snow.

In an example, the autonomous vehicle (“AV”) can be configured among the other vehicles and railway to communicate with a rider on a peer to peer basis to pick up the rider on demand from a location on a track, like a railway, tram or other track, rather than the rider being held hostage to a fixed railway schedule. The rider can have an application on his/her cell phone, which tracks each of the AVs, and contact them using the application on the cell phone. In an example, the AV is configured for both on-track and off track operation with different operating parameters for on-track and off track, including speed, degree of autonomy, sensors used etc.

A system for remote moisture monitoring and control includes: a measurement vehicle, including a vehicle body, a vehicle control unit, a transmitter antenna, and a receiver antenna; a moisture control server, including a processor, a non-transitory memory, an input/output, and antenna manager, a multi spectrum analyzer, a sensor manager, an irrigation manager, a soil simulator and a data bus; a vehicle storage facility; an irrigation controller; irrigation valves; a mobile control device; ground sensors. Also disclosed is a method including piloting measurement vehicle; obtaining moisture measurements, including controlling outbound transmission, determining reflected power, calculating dielectric constant via reflection calculation, determining soil moisture via lookup in soil calibration table; obtaining sensor measurements; calculating soil model; and adjusting irrigation.

In a columnar-shaped magnetic marker including a magnet formed by dispersing a magnetic powder of iron oxide in a polymer material and to be laid in a road without being accommodated in a metal container, one end face of an outer peripheral surface and an entire outer peripheral side surface of magnet are covered with metal foil forming a conductive layer, and an RFID tag which performs wireless communication with a tag reader mounted on a vehicle side is arranged on the end face of magnetic marker provided with metal foil as being in a state of being electrically insulated from metal foil.

A computer in a vehicle is configured to operate the vehicle in at least one of an autonomous and a semi-autonomous mode. The computer is further configured to detect at least one condition of a roadway being traveled by the vehicle, the condition comprising at least one of a restricted lane, a restricted zone, a construction zone, and accident area, an incline, a hazardous road surface. The computer is further configured to determine at least one autonomous action based on the condition, the at least one autonomous action including at least one of altering a speed of the vehicle, controlling vehicle steering, controlling vehicle lighting, transitioning the vehicle to manual control, and controlling a distance of the vehicle from an object.

A hybrid system of virtual walls and lighthouses for self-propelled apparatuses includes a self-propelled apparatus and a hybrid apparatus. The hybrid apparatus has a virtual-wall mode and a lighthouse mode. A first switch unit switches the hybrid apparatus to the virtual-wall mode or the lighthouse mode. The hybrid apparatus selectively being on one of a first detection mode, a second detection mode and a third detection mode emits first signals continuously. On the virtual-wall mode, after the self-propelled apparatus receives the first signal, the self-propelled apparatus walks away the block region of the hybrid apparatus. On the lighthouse mode, after the self-propelled apparatus receives the first signals, the self-propelled apparatus enters and then passes through the lighthouse region of the hybrid apparatus.

A self-propelled device is provided including a drive system, a spherical housing, and a biasing mechanism. The drive system includes one or more motors that are contained within the spherical housing. The biasing mechanism actively forces the drive system to continuously engage an interior of the spherical housing in order to cause the spherical housing to move.

An obstacle detection system for an agricultural work vehicle includes: an obstacle estimation unit 52 that estimates a region in a field based on a detection signal from an obstacle sensor 21 in which region an obstacle is present, and outputs obstacle present region information; an image capturing unit 22 that outputs a captured image of the field; an obstacle detection unit 54 that detects the obstacle from an input image and outputs obstacle detection information; and an image preprocessing unit 53 that generates, as an image to be input to the obstacle detection unit 54, a trimmed image obtained by trimming the captured image so as to include the region in which the obstacle is present, based on the obstacle present region information and shooting-angle-of-view information regarding the image capturing unit 22.