The present invention provides an improved, autonomous unmanned aircraft vehicle (UAV) for harvesting or diluting fruit, and a control unit for coordinating flight and/or harvesting missions thereof, as well as a system and method for harvesting fruits.

The application discloses a fruit picking method based on a three-dimensional parameter prediction model for a fruit. The method comprises: performing first-time image acquisition processing on a to-be-picked fruit to obtain a first image; determining a first range; controlling a manipulator to perform first-time moving processing; performing intermittent gas injection treatment to lead to forced vibration of the to-be-picked fruit; performing second-time image acquisition processing many times to obtain a plurality of second images; screening out, by taking the first image as an reference object, two appointed second images deviating from an equilibrium position to the maximum extent; jointly inputting the images into a preset three-dimensional parameter prediction model for the fruit so as to obtain predicted three-dimensional parameters; controlling the manipulator to perform second-time moving processing; and performing cutting processing on a fruit stem position to make the to-be-picked fruit fall onto the manipulator.

The application discloses a fruit picking method based on a three-dimensional parameter prediction model for a fruit. The method comprises: performing first-time image acquisition processing on a to-be-picked fruit to obtain a first image; determining a first range; controlling a manipulator to perform first-time moving processing; performing intermittent gas injection treatment to lead to forced vibration of the to-be-picked fruit; performing second-time image acquisition processing many times to obtain a plurality of second images; screening out, by taking the first image as an reference object, two appointed second images deviating from an equilibrium position to the maximum extent; jointly inputting the images into a preset three-dimensional parameter prediction model for the fruit so as to obtain predicted three-dimensional parameters; controlling the manipulator to perform second-time moving processing; and performing cutting processing on a fruit stem position to make the to-be-picked fruit fall onto the manipulator.

There is provided a mobile autonomous agricultural system comprising: a powered mobile unit for carrying agricultural equipment, and configured to move along rows of crops; at least one laser curtain sensor configured to project a laser curtain away from the mobile unit; a location module configured to monitor a location of the mobile unit relative to a row; a controller configured to control the travel of the mobile unit; a safety module configured to: receive a location signal from the location module related to the location of the mobile unit relative to a row, select a mode of operation to process the laser curtain in a predefined laser curtain pattern, based on the received location signal, each mode of operation corresponding to a different predefined laser curtain pattern, and to generate a safety output in response to determining that the laser curtain is interrupted within the laser curtain pattern.

There is provided a mobile autonomous agricultural system comprising: a powered mobile unit for carrying agricultural equipment, and configured to move along rows of crops; at least one laser curtain sensor configured to project a laser curtain away from the mobile unit; a location module configured to monitor a location of the mobile unit relative to a row; a controller configured to control the travel of the mobile unit; a safety module configured to: receive a location signal from the location module related to the location of the mobile unit relative to a row, select a mode of operation to process the laser curtain in a predefined laser curtain pattern, based on the received location signal, each mode of operation corresponding to a different predefined laser curtain pattern, and to generate a safety output in response to determining that the laser curtain is interrupted within the laser curtain pattern.

A human-robot system and method for performing an agricultural task, the system including: a robotic manipulator with an agricultural tool coupled to an end effector thereof; an imaging device adapted to capture imagery of a target, the imaging device mechanically coupled to the end effector; a laser distance sensor adapted to measure a distance between the manipulator and the target, the laser distance sensor mechanically coupled to the end effector and collocated with the imaging device; and a control unit including: a processing unit, a monitor and a human-machine interface (HMI), wherein the processing unit is configured to display the imagery on the monitor and to receive markings from the HMI and calculate a trajectory for the manipulator to perform the agricultural task with the tool.

A human-robot system and method for performing an agricultural task, the system including: a robotic manipulator with an agricultural tool coupled to an end effector thereof; an imaging device adapted to capture imagery of a target, the imaging device mechanically coupled to the end effector; a laser distance sensor adapted to measure a distance between the manipulator and the target, the laser distance sensor mechanically coupled to the end effector and collocated with the imaging device; and a control unit including: a processing unit, a monitor and a human-machine interface (HMI), wherein the processing unit is configured to display the imagery on the monitor and to receive markings from the HMI and calculate a trajectory for the manipulator to perform the agricultural task with the tool.

The present invention provides a device and a method for picking and collecting Brasenia schreberi based on a machine vision. The device for picking and collecting Brasenia schreberi includes a supporting mechanical arm, a collection device, two working mechanical arms, a picking manipulator, a grasping manipulator, a control box, and a visual system. The supporting mechanical arm is fixed on a front end of a boat; the two working mechanical arms are fixed on a front end of the supporting mechanical arm; the picking manipulator and the grasping manipulator are mounted on tail ends of the two working mechanical arms, respectively; and the collection device is fixed on the boat; the visual system determines a location of the Brasenia schreberi and sends the location to the control box; the control box controls the two working mechanical arms, the grasping manipulator, and the picking manipulator to complete the grasping and picking of the Brasenia schreberi; and then the collection device collects the Brasenia schreberi.

Unmanned aerial vehicles (UAVs) may be configured and deployed to maintain inventory and retrieve products for delivery. The UAVs can be equipped with a plurality of sensors used to assess the condition of inventory items, report the condition to a central control, and to retrieve inventory items. The UAVs can scan fruits and vegetables, for example, to determine the current ripeness. The UAV can then harvest the items if ready or provide a status update if they are not ready. The UAVs can be used in conjunction with transporters and harvesters to deliver products from the field or warehouse to a central control or directly to the customer. In scanning the products for readiness, the UAVs can also detect issues such as spoilage, fungus, and pests. This information can be used for the specific application of treatments.

Unmanned aerial vehicles (UAVs) may be configured and deployed to maintain inventory and retrieve products for delivery. The UAVs can be equipped with a plurality of sensors used to assess the condition of inventory items, report the condition to a central control, and to retrieve inventory items. The UAVs can scan fruits and vegetables, for example, to determine the current ripeness. The UAV can then harvest the items if ready or provide a status update if they are not ready. The UAVs can be used in conjunction with transporters and harvesters to deliver products from the field or warehouse to a central control or directly to the customer. In scanning the products for readiness, the UAVs can also detect issues such as spoilage, fungus, and pests. This information can be used for the specific application of treatments.