A method may include comparing, using a virtual map, a position of a vehicle to a position of an obstacle in an operating environment; and adjusting a trajectory of the vehicle to avoid the obstacle. A method may include receiving, from a sensor of a vehicle, data associated with an operating environment of the vehicle; identifying an object in the operating environment based on the data; classifying the object based on an object recognition process; and assigning a clearance envelope to the object based on the classification of the object. A method may include querying a virtual map of an operating environment, the virtual map including a characteristic for an object within the operating environment; and maintaining, by a vehicle, a clearance envelope with respect to the object based on the object characteristic. Additional methods and associated systems are also disclosed.

The present application relates to the technical field of self-propelled devices, and discloses a method for preventing a self-propelled device from falling. The method comprises: determining an environmental map corresponding to an operating environment and a historical trigger record of the cliff sensor in the operating environment based on at least one task execution result of the self-propelled device in the operating environment, wherein the environmental map is marked with an unreachable region; determining a task activity forbidden region for the self-propelled device based on the unreachable region and the historical trigger record; and controlling the self-propelled device to perform a preset task outside the task activity forbidden.

Systems and methods include: a mobile robot comprising a drive system, at least one image sensor; at least one infrared sensor, and an onboard processing system having at least one processor and a memory storing instructions; a store gateway communicatively coupled to the mobile robot and configured to receive an event record under a bandwidth-aware policy, to provide at least aspects of the event record for upload for storage to a cloud service, and to receive updates from the cloud service for the mobile robot; and an analytics module at the cloud service communicatively coupled to the store gateway and configured to perform analytics of uploaded ones of the event records.

A control method for an automatic cleaning device includes detecting a second obstacle ahead of the automatic cleaning device during movement of the automatic cleaning device along a first obstacle, acquiring a length of the second obstacle in response to the second obstacle being present ahead of the automatic cleaning device, and controlling a movement path of the automatic cleaning device based on the length of the second obstacle.

A computer-implemented method and system for planning the behavior of a vehicle in a traffic scene. The behavior planning pursues a specified destination. The system includes a perception level for aggregating scene-specific information and for generating at least one scene representation of the traffic scene, a neural network which carries out strategic behavior planning based on the scene representation generated by the perception level, and a downstream planning component which carries out detailed behavior planning based on the strategic behavior planning. The neural network is trained to generate a geometric behavior specification for the vehicle in the given traffic scene as a result of the strategic behavior planning. For this purpose, the neural network identifies at least one go zone that the vehicle may or should pass through to pursue the specified destination, and/or at least one no-go zone that the vehicle should avoid when pursuing the specified destination.

An apparatus for generating a semantic map-based robot driving route plan for transportation vulnerable includes: a semantic map generation unit configured to generate a semantic map for an area where a driving robot is driving based on real-time location tracking data of the driving robot and semantic data on a surrounding environment; a safety zone generation unit configured to calculate heights for a plurality of objects recognized while the driving robot is driving on the generated semantic map and generate a safety zone for a specific object determined to be the transportation vulnerable among the plurality of objects based on the heights; and a driving route plan generation unit configured to generate a second driving route plan different from a first driving route plan in real time for the safety zone when the safety zone is generated while the driving robot is driving with the first driving route plan.

Disclosed is a method and system for dynamic obstacle avoidance in unmanned aerial vehicles (UAVs). The approach involves dynamically modifying an obstacle margin based on detected conditions to enable navigation through confined areas. It includes automatically shrinking the obstacle margin when the UAV is in a reduced obstacle mode and limiting the maximum speed of the UAV to a predetermined value in this mode. The system also reduces the size of an obstacle map to enhance resolution and improve detection of confined spaces. Additionally, it dynamically determines detected conditions to automatically adjust the level of obstacle avoidance and detects when the reduced obstacle mode can be exited, allowing the UAV to return to a previous mode.

An unmanned vehicle includes: a travel device; an obstacle sensor; a host path storage unit that stores a host path; a travel control unit that controls the travel device based on the host path; an oncoming path storage unit that stores an oncoming path to be given to an oncoming vehicle; and an obstacle presence/absence determination unit that determines whether or not an obstacle is located on the oncoming path based on detection data from the obstacle sensor.

A mechanism for defining an alert zone surrounding an agricultural vehicle. The size and/or shape of side zones, that span alongside the agricultural vehicle, of the alert zone are defined or modified responsive to one or more characteristics of an implement that is being towed by the agricultural vehicle.

An autonomous moving system according to the present disclosure is an autonomous moving system including an autonomous moving body that moves autonomously. The autonomous moving system includes a control unit that executes control of movement of the autonomous moving body including collision control, a setting unit that sets a defense space around the autonomous moving body, for executing the collision control, a detecting unit that detects obstructions in a vicinity of the autonomous moving body, and a classifying unit that classifies obstructions that are detected. The setting unit changes a range of the defense space, based on the obstructions that are classified by the classifying unit, and the control unit executes control of movement of the autonomous moving body including the collision control in at least one of when the obstruction is inside the defense space and when the obstruction is predicted to enter the defense space.