In a work management device and a work management method, in the case where the number of autonomous mobile working machines used in performing work has been changed, or in the case where, among a plurality of assigned working regions, a difference that is greater than or equal to a percentage threshold value has occurred in a work completion percentage, which is a ratio of a portion where the work is completed to each of the assigned working regions, resetting of the assigned working regions is carried out.

An autonomous lawn mower is described. The autonomous lawn mower comprises a chassis supporting a podium that is raked forward with respect to a horizontal plane. In some examples, the podium comprises a top portion that may support one or more sensors, antennas and/or cameras that may be used to provide environmental information regarding the surroundings of the autonomous lawn mower. In additional or alternative examples, the podium may facilitate communication services to and/or from the autonomous lawn mower. Such a podium may improve the operation of the mower by a user when manually (or semi-autonomously controlled) while optimizing a field of view of such sensors with respect to the mowable area.

A moving object control system that controls an operation of a moving object obtains information of a sensor configured to recognize a periphery of the moving object, generates a dynamic prediction map including information indicating a position of a static obstacle recognized based on the information of the sensor and information indicating a position of a dynamic obstacle that changes with time and is recognized based on the information of the sensor, and generates a target trajectory for controlling traveling of the moving object by using the generated dynamic prediction map.

The present disclosure provides a cleaning robot and a movement control method thereof. Based on the method, during travel of the cleaning robot, three-dimensional information of an obstacle is acquired through a sensor system. When the obstacle moves within the detection range of the sensor system, when a distance between the obstacle and the cleaning robot along a central axis of the cleaning robot is less than a first preset detection threshold, and when a maximum value among included angles between connection lines constituted by a first reference point of the cleaning robot and second reference points of the obstacle and a current traveling direction of the cleaning robot is greater than a third preset detection threshold, an action away from the obstacle is intelligently performed.

An autonomous lawn mower is described. The autonomous lawn mower comprises a chassis supporting a podium. In some examples, the podium comprises a top portion that may support one or more sensors, antennas and/or cameras that may be used to provide environmental information regarding the surroundings of the autonomous lawn mower. In additional or alternative examples, the autonomous lawn mower receives, via a wireless receiver, a signal from a remote controller, the signal comprising one or more of an emergency stop signal or a pause signal. Based at least in part on the signal comprising the emergency stop signal, causing the autonomous lawn mower to invoke an emergency stop procedure, or based at least in part on the signal comprising the pause signal, causing the autonomous lawn mower to invoke a pause procedure.

The described positional awareness techniques employing visual-inertial sensory data gathering and analysis hardware with reference to specific example implementations implement improvements in the use of sensors, techniques and hardware design that can enable specific embodiments to provide positional awareness to machines with improved speed and accuracy.

Systems and methods for autonomous vehicle path planning are described herein. An example vehicle includes an image sensor to obtain an image of a scene of an area surrounding the vehicle. The vehicle also includes navigation system circuitry to: analyze the image and generate a semantically segmented image that identifies one or more types of features in the image; project the semantically segmented image to a two-dimensional (2D) map projection; convert the 2D map projection into a cost map; and determine a path for the vehicle based on the cost map.