Patent classifications
G05D1/617
Path planning using sparse volumetric data
A view of geometry captured in image data generated by an imaging sensor is compared with a description of the geometry in a volumetric data structure. The volumetric data structure describes the volume at a plurality of levels of detail and includes entries describing voxels defining subvolumes of the volume at multiple levels of detail. The volumetric data structure includes a first entry to describe voxels at a lowest one of the levels of detail and further includes a number of second entries to describe voxels at a higher, second level of detail, the voxels at the second level of detail representing subvolumes of the voxels at the first level of detail. Each of these entries include bits to indicate whether a corresponding one of the voxels is at least partially occupied with the geometry. One or more of these entries are used in the comparison with the image data.
Method for operating a picking device for medicaments and a picking device for carrying out said method
Picking devices for operating a picking devices for medicaments are provided. A picking device includes multiple storage spaces for medicament packaging, an operating device movable horizontally in an X-direction and vertically in a Z-direction in front of the storage spaces in a movement space, and an identification device configured for identifying medicament packaging. An optical detection device is configured to create an overall image of the movement space and a control device is coupled to the operating device, the identification device and the optical detection device, wherein the control device is configured to determine the presence of an obstacle in a portion of the movement space and to control the operating device based on the determined presence of the obstacle. Methods of operating picking devices for medicaments are also provided.
Fleet management of unmanned aerial vehicles and flight authorization system
Methods, systems and apparatus, including computer programs encoded on computer storage media for fleet management of unmanned aerial vehicles, including flight authorization. One of the methods includes maintaining one or more rules associated with authorizing UAVs to implement flight plans. A request to generate a flight plan associated with a job is received, the request including information indicating a flight pattern comprising, at least, one or more waypoints associated with geospatial references. The flight plan is generated based on the request, and an initial authorization check is determined based on the maintained rules and the generated flight plan. Upon a positive determination, access to the generated flight plan is provided by a ground control system, and the flight plan is implemented.
Dynamic probabilistic motion planning
Techniques and systems are disclosed for using swept volume profile data cached in association with a PRM to improve various aspects of motion planning for a robot. In some implementations, a first probabilistic road map representing possible paths to be travelled by a robot within a physical area is generated. An initial path for the robot within the first probabilistic road map is determined. Data indicating a second probabilistic road map representing a path to be travelled by a movable object within the physical area is obtained. A potential obstruction associated with one or more edges included in the subset of edges is detected. An adjusted path for the robot within the first probabilistic road map is then determined based on the potential obstruction.
Sun-aware routing and controls of an autonomous vehicle
Sun-aware routing and controls of an autonomous vehicle is described herein. A location and an orientation of a sensor system is identified within an environment of the autonomous vehicle to determine whether the sun causes a threshold level of perception degradation to the sensor system incident to generating a sensor signal indicative of a traffic light. The determination is based upon perception degradation data that can be precomputed for locations and orientations within the environment for dates and times of day. The perception degradation data is based upon the location of at least one traffic light and positions of the sun relative to the locations and the orientations within the environment. A mechanical system of the autonomous vehicle is controlled to execute a maneuver that reduces perception degradation to the sensor system when the perception degradation is determined to exceed the threshold level of perception degradation.
Autonomous driving vehicle that avoids natural disasters
An autonomous driving vehicle provides a driverless transportation service for a user. An alarming phenomenon is a natural phenomenon that potentially causes a disaster. The autonomous driving vehicle recognizes, based on driving environment information, the alarming phenomenon at a current location of the autonomous driving vehicle or on a planned travel route from the current location to a destination. When recognizing the alarming phenomenon, the autonomous driving vehicle determines whether to continue or halt vehicle travel control in accordance with a current travel plan. When determining to halt the vehicle travel control in accordance with the current travel plan, the autonomous driving vehicle sets an emergency plan depending on a type of the alarming phenomenon and controls the autonomous driving vehicle in accordance with the emergency plan.
System including conveyance vehicle and work machine that loads materials onto conveyance vehicle, method and work machine
A system includes a conveyance vehicle, and a work machine that loads materials onto the conveyance vehicle. A first processor of a work machine determines a target stop position of a conveyance vehicle based on a position of the work machine, a target offset distance, and the direction of the loading position. A second processor of the conveyance vehicle acquires data indicative of the target stop position of the conveyance vehicle from the work machine. The second processor controls the conveyance vehicle to move the conveyance vehicle to the target stop position.
System including conveyance vehicle and work machine that loads materials onto conveyance vehicle, method and work machine
A system includes a conveyance vehicle, and a work machine that loads materials onto the conveyance vehicle. A first processor of a work machine determines a target stop position of a conveyance vehicle based on a position of the work machine, a target offset distance, and the direction of the loading position. A second processor of the conveyance vehicle acquires data indicative of the target stop position of the conveyance vehicle from the work machine. The second processor controls the conveyance vehicle to move the conveyance vehicle to the target stop position.
Interaction management in an online agricultural system
An online agricultural system manages and optimizes interactions of entities within the system to enable the execution of transaction and the transportation of crop products. The online agricultural system accesses historic and environmental data describing factors that may impact crop product transactions and/or transportation to determine market prices for crop products and crop product transportation. Responsive to receiving a request from an entity, the online agricultural system determines an optimal transaction for the entity, such as a price for selling a crop product, an available crop product for purchase, or a transportation opportunity to transport a crop product.
System and method for autonomous operation of a machine
A system for autonomous or semi-autonomous operation of a vehicle is disclosed. The system includes a machine automation portal (MAP) application configured to enable a computing device to (a) display a map of a work site and (b) provide a graphical user interface that enables a user to (i) define a boundary of an autonomous operating zone on the map and (ii) define a boundary of one or more exclusion zones. The system also includes a robotics processing unit configured to (a) receive the boundary of the autonomous operating zone and the boundary of each exclusion zone from the computing device, (b) generate a planned command path that the vehicle will travel to perform a task within the autonomous operating zone while avoiding each exclusion zone, and (c) control operation of the vehicle so that the vehicle travels the planned command path to perform the task.