An adaptive manipulation apparatus and method are provided. The adaptive manipulation method includes steps of providing a mobile manipulation apparatus comprising a manipulator, a sensor and a processor for a manipulation of an object placed on a carrier having a plurality of markers spaced apart from each other, the sensor detecting the plurality of markers to obtain a run time marker information, the processor, according to the base-case motion plan, generating a run time motion plan, wherein the run time motion plan comprises a plurality of second pose-aware actions, and the plurality of second pose-aware actions are modified from the plurality of first pose-aware actions according to the run time marker information, and the processor further executing the run time motion plan for controlling the manipulator to manipulate the object.

A modular control system for controlling an AGV includes an interface, a processor, a memory, and a plurality of programs. The plurality of programs include a task scheduling module, a sensor fusion module, a mapping module, and a localization module. The interface receives a command signal from an AGV management system and sensor signals from a plurality of sensors. The memory stores a surrounding map and the plurality of programs to be executed by the processor. The task scheduling module converts the command signal to generate an enabling signal. The sensor fusion module processes the received sensor signals according to the enabling signal and generates an organized sensor data. The mapping module processes the organized sensor data and the surrounding map to generate an updated surrounding map. The localization module processes the organized sensor data and the updated surrounding map to generate a location and pose signal.

A control method performed by a controller includes calculating times required for a worker to load, on an automated guided vehicle, multiple articles placed in multiple locations regarding multiple cases among which a stop situation of the automated guided vehicle where the worker loads the articles varies and determining a position in which the automated guided vehicle is to be stopped, based on the calculated times.

The disclosure is directed to a method for controlling a vehicle in a depot. The method includes the steps: allocating a three-dimensional target object to the vehicle; detecting a three-dimensional object in the environment around the vehicle and determining depth information for the detected three-dimensional object; classifying the detected three-dimensional object on the basis of the determined depth information and checking whether the determined three-dimensional object has the same object class as the three-dimensional target object; identifying the detected three-dimensional object if the determined three-dimensional object has the same object class as the three-dimensional target object by detecting an object identifier assigned to the three-dimensional object and checking whether the detected object identifier matches a target identifier assigned to the target object; outputting an approach signal to move the vehicle closer to the detected three-dimensional target object in an automated manner or manually if the object identifier matches the target identifier.

A forklift truck includes a main controller, a driving motor, a drive controller, and an object detector. The drive controller controls the driving motor. The object detector detects the position of an object being present in the backward direction of the forklift truck. The main controller derives an expected trajectory of the forklift truck. The main controller imposes a speed limit on the forklift truck by setting a vehicle speed upper limit when the object detected by the object detector is located within the expected trajectory and the forklift truck is traveling in the direction of approaching the object. The main controller gives commands to the drive controller to prevent the vehicle speed of the forklift truck from exceeding the vehicle speed upper limit.

A method and an apparatus for generating sensor data for controlling an autonomous vehicle in an environment is provided, such as driverless transport vehicles in a factory for example. Sensor positions of static sensors and the sensors of autonomous vehicles are defined in a global coordinate system on the basis of an environment model, such as a BIM model for example. Sensor data is centrally generated in this global coordinate system for all sensors as a function of these sensor positions. The sensor data is then transformed into a local coordinate system of an autonomous vehicle and transferred for controlling the autonomous vehicle.

A method includes: obtaining a batch of item group definitions, each item group definition having one or more item identifiers and corresponding quantities; for each item identifier, retrieving (i) a location of a corresponding item in a facility, and (ii) a dimensional attribute of the corresponding item; based on the locations and dimensional attributes, assigning sets of the item group definitions to respective receptacle configurations, each receptacle configuration including, for each item group definition in the set, a receptacle type with a predefined capacity; monitoring availability of a plurality of transporters in the facility, each transporter having a chassis configured to support a selectable set of receptacles; and responsive to detecting that a transporter is available, selecting one of the receptacle configurations, and presenting the selected receptacle configuration via an output device, to initiate placement of receptacles onto the chassis of the transporter according to the selected receptacle configuration.

A system, in particular a manufacturing system, the system including machines, especially stationary and mobile machines, and at least one vehicle and a control, the vehicle having at least one sensor for ascertaining the relative position of a person, in particular a sensor for ascertaining the distance between the vehicle and the person, and for ascertaining the angle between the driving direction of the vehicle and the connecting line between the person and the vehicle, the vehicle having a position acquisition means for sensing the position of the vehicle, in particular a GPS system or a triangulation system for ascertaining the position of the vehicle, the control including a means for ascertaining the safety zone around the person and the machines situated therein, a data transmission channel being provided between the control and the machines.

A device includes an external sensor to scan an environment so as to periodically output scan data, a storage to store an environmental map, and a location estimation device to match the sensor data against the environmental map read from the storage so as to estimate a location and an attitude of the vehicle. The location estimation device determines predicted values of a current location and a current estimation of the vehicle in accordance with a history of estimated locations and estimated attitudes of the vehicle, and performs the matching by using the predicted values.

An autonomous robotic system, and method for automatically monitoring the state of shelves in stores, like retail stores or supermarkets are based on a mobile The mobile robot is capable of autonomously navigating the aisles of a store, with the ability to monitor the condition of product shelves. Specifically, the robotic system solves problems associated with the operation of the shelves, mainly with respect to the detection of incorrect or missing price signs, verification of offer signs, detection of product stock, estimation of product layout, and identification of products misplaced or with errors in the spatial extent assigned to the supplier on a shelf.