Abstract: A system, including: a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations including: detecting a first automobile; determining that the first automobile is a self-driving automobile; and in response to determining that the first automobile is a self-driving automobile, causing a second automobile to emulate a motion of the first automobile.

Abstract: State estimation and sensor fusion switching methods for autonomous vehicles thereof are provided. The autonomous vehicle includes at least one sensor, at least one actuator and a processor, and is configured to transfer and transport an object. In the method, a task instruction for moving the object and data required for executing the task instruction are received. The task instruction is divided into a plurality of work stages according to respective mapping locations, and each of the work stages is mapped to one of a transport state and an execution state, so as to establish a semantic hierarchy. A current location of the autonomous vehicle is detected by using the sensor and mapped to one of the work stages in the semantic hierarchy, so as to estimate a current state of the autonomous vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robot motion planning using unmanned aerial vehicles (UAVs). One of the methods includes determining that a current plan for performing a particular task with a robot requires modification; in response, generating one or more flight plans for an unmanned aerial vehicle (UAV) based on a robotic operating environment comprising the robot; obtaining, using the UAV in accordance with the one or more flight plans, a new measurement of the robotic operating environment comprising the robot; and generating, based at least on a difference between the new measurement of the robotic operating environment and a previous measurement of the robotic operating environment, a modified plan for performing the particular task with the robot.

Abstract: A location of an occupant within a vehicle and/or an activity engaged in by the occupant may be determined. Based on the location and/or the activity, a point of interest associated with the occupant and/or the vehicle may be determined. One or more systems of the vehicle, such as the steering and/or suspension, may be controlled to minimize acceleration associated with the point of interest, thereby increasing a comfort of the occupant. In instances where the vehicle includes more than one occupant, the vehicle may be adjusted to accommodate the multiple occupants.

Abstract: This application relates to apparatus and methods for automatic delivery route generation and assignment. In some examples, a computing device determines delivery locations for each of a plurality of previous routes taken by each of a plurality of drivers over a period of time. The computing device also obtains a plurality of current routes to be assigned to the plurality of drivers. Further, the computing device determines a familiarity value for each of the plurality of drivers for each of the plurality of current routes based on the delivery locations of the previous routes taken by each driver. The computing device assigns each of the plurality of drivers to a current route based on the determined familiarity values, and stores the assignments in a data repository. In some examples, the computing device transmits the assignments to another computing device, such as a computing device of each driver.

Abstract: A movement control method for a multi-vehicle system for moving multiple vehicles to target positions individually set for the vehicles includes: acquiring first positions of the vehicles; determining control input for moving the vehicles from the first positions to second positions away from the target positions by a first distance or more while the vehicles satisfy a predetermined condition; and updating the first distance to be a shorter distance when a distance between the second position and the target position of each of the vehicles becomes equal to or more than the first distance and within an updating distance.

Abstract: Systems and methods for remotely controlling a system using video are provided. A method in accordance the present disclosure includes detecting a video signal of an auxiliary system at a video input, wherein the video signal including images encoded with control information. The method also includes determining that the images included in the video signal include the control information. The method further includes extracting the control information from the images. Additionally, the method includes modifying operations of the system based on the control information.

Abstract: A robot including a driver configured to move a main body, a memory configured to store an obstacle map with respect to a cleaning area, a sensor configured to collect information about the cleaning area, a communication interface configured to communicate with a second robot, and a controller is disclosed. The controller is configured to, when receiving an obstacle map including position information for a liquid region in the cleaning area from the second robot, control the main body to move to the liquid region and clean the liquid region.

Abstract: A method including determining a total amount of unprocessed material that has been dumped into the material processing device during a first time period determining a total amount of unprocessed material that has been processed during the first time period; determining a reference level of unprocessed material at the first point in time; predicting, based on the current level of unprocessed material contained in the material processing device and on an expected future processing rate of the material processing device at least one of an earlier and a later point in time at which the level of unprocessed material is expected to fall below a lower or upper limit; establishing a desired time-of-arrival period extending between a start point and an end point corresponding to the earlier and later points in time respectively; and adapting a speed of the first load-carrying vehicle.

Abstract: A method includes generating a training data set comprising a plurality of training examples, wherein each training example is generated by receiving map data associated with a road portion, receiving sensor data associated with a road agent located on the road portion, defining one or more corridors associated with the road portion based on the map data and the sensor data, extracting a plurality of agent features associated with the road agent based on the sensor data, extracting a plurality of corridor features associated with each of the one or more corridors based on the sensor data, and for each corridor, labeling the training example based on the position of the road agent with respect to the corridor, and training a neural network using the training data set.

Abstract: An unmanned aerial vehicle (UAV) or “drone” executes a neural network to assist with inspection, surveillance, reporting, and other missions. The drone inspection neural network may monitor, in real time, the data stream from a plurality of onboard sensors during navigation to an asset along a preprogrammed flight path and/or during its mission (e.g., as it scans and inspects an asset).

Abstract: Techniques are described herein for generating trajectories for autonomous vehicles using velocity-based steering limits. A planning component of an autonomous vehicle can receive steering limits determined based on safety requirements and/or kinematic models of the vehicle. Discontinuous and discrete steering limit values may be converted into a continuous steering limit function for use during on-vehicle trajectory generation and/or optimization operations. When the vehicle is traversing a driving environment, the planning component may use steering limit functions to determine a set of situation-specific steering limits associated with the particular vehicle state and/or driving conditions. The planning component may execute loss functions, including steering angle and/or steering rate costs, to determine a vehicle trajectory based on the steering limits applicable to the current vehicle state.

Abstract: Among other things, a vehicle drives autonomously on a trajectory through a road network to a goal location based on an automatic process for planning the trajectory without human intervention; and an automatic process alters the planning of the trajectory to reach a target location based on a request received from an occupant of the vehicle to engage in a speed-reducing maneuver.

Abstract: A moving robot includes: a sensor to acquire terrain information; a memory to store node data for at least one node; and a controller, and the controller determines whether at least one open movement direction exists among a plurality of movement directions, based on sensing data and the node data, generates a new node in the node data when at least one open movement direction exists, determines any one of the open movement directions as a traveling direction for the robot, determines whether at least one of the nodes needs to be updated exists, based on the node data when the open movement direction does not exist, controls the moving robot to move to one of the nodes that need to be updated, and generates of a map including the at least one node, based on the node data, when the node that needs to be updated does not exist.

Abstract: A method including determining a direct distance between the vehicle position and a position of the roadside unit and a planar distance between the vehicle position in a horizontal plane containing the vehicle position, and a projection of the position of the roadside unit onto the plane. The method further includes calculating a height of a roadside unit relative to the vehicle position using the direct distance and the planar distance determined for the vehicle position. The method also includes setting a value indicative of the height of the roadside unit relative to the vehicle position as a height correction value and storing the height correction value of the vehicle position in association with information indicative of the vehicle position as the height correction function.

Abstract: Techniques are provided for generating a driving trajectory for a vehicle while the vehicle is blocked (e.g., the sensor of the vehicle have detected an object results in the vehicle being unable to move) by an object (e.g., another vehicle, bicycle, or a pedestrian) and executing the driving trajectory when the vehicle becomes unblocked. In addition, techniques are provided for updating a portion of a driving trajectory of a vehicle based on a determination that an object will cross a segment of the current driving trajectory at a later point, without recalculating the whole trajectory.

Abstract: One embodiment of the present invention provides an intersection point pattern recognition system using sensor data of a mobile robot, comprising: a mobile robot that autonomously drives by using sensor data received from a sensor unit and an intersection point pattern recognition model provided by a management server; and the management server that receives usage environment information of the mobile robot and generates the intersection point pattern recognition model of the mobile robot to provide the intersection pattern recognition model to the mobile robot, wherein the management server comprises: a map generation unit for receiving the usage environment information of the mobile robot and generating a route map of the mobile robot on the basis of the usage environment information; a normalization unit for generating a virtual map by normalizing the route map according to a preset rule; and a learning unit for generating the intersection point pattern recognition model by using the virtual map and the se

Abstract: Systems and techniques for detecting a difference in orientation between a lawn mower and a surface on which the mower is mowing, or between portions of such surface, based on one or more of sensor data or map data are discussed. The difference in orientation may then be used to control the lawn mower by, for example, raising a deck height or idling a blade speed, though other actuations are contemplated. In some examples, an amount the deck height is raised may be based on the difference in orientation. Based on a subsequent difference detected being at or below a threshold difference, the mower may return to previous operating conditions including, but not limited to, returning a blade speed to a previous blade speed and/or returning the deck height to a previous deck height, among other controls.

Abstract: A vehicle for predicting a risk of collision includes a controller configured to: calculate distances between the vehicle and left and right lines of a first lane, respectively, using a position of the vehicle and first lane width information of the first lane, calculate distances between the surrounding vehicle and left and right lines of a second lane, respectively, using a position of the surrounding vehicle and second lane width information of the second lane, calculate a second distance between the vehicle and the surrounding vehicle by reflecting the calculated distances between the vehicle and the left and right lines of the first lane or the calculated distances between the surrounding vehicle and the left and right lines of the second lane to a first distance, and predict a risk of collision between the vehicle and the surrounding vehicle based on the second distance.

Abstract: An operation method of an optimal route searching device includes: acquiring topology transformed map information; extracting a plurality of candidate routes based on the topology transformed map information; calculating a travel cost for each of the plurality of candidate routes based on a cost function; and determining a candidate route corresponding to a lowest cost one of the calculated travel costs as a travelling route.

Abstract: A method teaches at least one section of a delimiting border of a land area for a green area maintenance system. The green area maintenance system has: an autonomous mobile green area maintenance robot, and a robot position determining system. The robot position determining system is designed to detect robot position coordinates of the green area maintenance robot. The robot position coordinates are based on a first position determining technology. The method (a) defines a sequence of teach-in position coordinates of the section, the teach-in position coordinates being based on a second position determining technology different from the first position determining technology, and (b) transforms the defined sequence of teach-in position coordinates into a sequence of transformation robot position coordinates, the transformation robot position coordinates being based on the first position determining technology.

Abstract: System, methods, and other embodiments described herein relate to improving the training of a driver during an automated driving system mode. In one embodiment, a method includes generating, in association with a maneuver by the driver that is a takeover of a vehicle, an automated motion plan associated with the maneuver. The method also includes determining if the automated motion plan is valid based, at least in part, on a condition that one or more parameters of a reliability model satisfy a threshold. The one or more parameters may be associated with the vehicle and a driving environment. The method also includes notifying the driver that the maneuver was unnecessary using a notification signal if the one or more parameters satisfy the threshold.

Abstract: A server includes a controller configured to control operation of a vehicle, and a communication interface configured to communicate with a terminal apparatus held by a first user. The communication interface acquires, from the terminal apparatus, a list including a vehicle designation condition designated by the first user when the first user reserves boarding of a vehicle. The controller determines a vehicle to be boarded by the first user based on the list.

Abstract: A communication system including a mobile station that communicates with a wireless station and moves toward a predetermined destination, and a relay station that relays communication between the mobile station and the wireless station, includes: the mobile station that pauses movement when sensing an obstacle present on a first moving route toward the destination in a case of moving along the first moving route, and moves along a second moving route headed to the destination while avoiding the obstacle when establishing communication between the mobile station and the wireless station via the relay station in a case where the movement is paused; and the relay station that moves so as to keep a position where communication between the mobile station and the wireless station can be relayed according to movement of the mobile station when the mobile station moves along the second moving route.

Abstract: A path setting apparatus that sets a path of a mobile body having a plurality of operation modes is provided. The apparatus includes a quality acquisition unit configured to acquire communication qualities at a plurality of geographical locations, and a setting unit configured to set a path of the mobile body so as to pass through an area that satisfies a requirement of communication quality that is determined according to an operation mode of the mobile body.

Abstract: A system for controlling an overtake maneuver of a control vehicle comprises a controller structured to determine an overtake velocity for the control vehicle traveling in a vehicle lane to overtake a front vehicle traveling ahead of the control vehicle in the vehicle lane. The controller determines an overtake time for the control vehicle to overtake the front vehicle based on the overtake velocity. The controller determines a direction of traffic in an overtake lane that is adjacent to the vehicle lane. If the direction of traffic in the overtake lane is the same as a direction of traffic in the vehicle lane, and the overtake velocity is less than or equal to an allowed velocity, the controller executes the overtake maneuver by one of adjusting a parameter of an engine and/or a transmission of the control vehicle or providing a command to an operator of the control vehicle.

Abstract: Achieved is an autonomous traveling control device which generates a safety priority path for avoiding passage through or approach to a dangerous region where a contact with another mobile object is possible, and travels along the safety priority path. The autonomous traveling control device includes a traveling path determination unit that generates a safety priority path for avoiding passage through or approach to a dangerous region where a contact with another mobile object is possible; and a traveling control unit that executes control causing the own device to travel along the safety priority path generated by the traveling path determination unit. The traveling path determination unit generates a cost priority path in a metric map on the basis of a minimum cost path in a topology map, and generates a safety priority path bypassing the dangerous region by correcting the cost priority path in the metric map.

Abstract: A charging system for an autonomous data machine may be provided. The system may comprise: a charging station, wherein the charging station has a low profile allowing the autonomous data machine to drive over to charge a power supply of the autonomous data machine automatically; and one or more processors of the autonomous data machine configured to make charging decisions to effect charging operations of the autonomous data machine that include charging time, charging location, and operations to be performed during charging. In some instances, the charging decision are based on at least one of the following: location of charging station, availability of charging station, mission parameters, locations of other autonomous data machines, and/or charging requirements and/or availability of charging stations.

Abstract: Present embodiments describe a method for controlling a robotic vehicle that can include causing a processor to determine a localized position of a dynamic object, determining, via the processor, a predicted trajectory of the robotic vehicle based on the localized position of the dynamic object, and determining an optimum trajectory based on the predicted trajectory, the optimum trajectory chosen based a travel velocity and longitudinal velocity. Determining the optimum trajectory can include computing a cost value comprising a plurality of cost terms associated with the optimum trajectory, and determining a control command that modifies a travel velocity and a travel vector of the robotic vehicle based on the cost value. The method further includes causing, via the processor, the robotic vehicle to follow the optimal trajectory based on the control command.

Abstract: A driving control method comprises: acquiring a destination of a vehicle; referring to a first map that includes identification information of a travel lane and a second map that does not include the identification information of the travel lane; calculating a route from a current position of the vehicle to the destination; when traveling along a first route included in the route and belonging to the first map, setting first driving control, while when traveling along a second route included in the route and belonging to the second map, setting second driving control with a lower level of autonomous driving than that of the first driving control; and creating a driving plan for the vehicle to travel along the route with contents of the set driving control. A driving control apparatus is based on the method.

Abstract: In one embodiment, a computer-implemented method of operating an autonomous driving vehicle (ADV) includes perceiving a driving environment surrounding the ADV based on sensor data obtained from one or more sensors mounted on the ADV, determining a driving scenario, in response to a driving decision based on the driving environment, applying a predetermined machine-learning model to data representing the driving environment and the driving scenario to generate a set of one or more driving parameters, and planning a trajectory to navigate the ADV using the set of the driving parameters according to the driving scenario through the driving environment.

Abstract: A transfer device includes a controller configured or programmed to perform at least one of a first control to make a maximum acceleration when moving a FOUP to a front end side smaller than a maximum acceleration when moving to a back end side, a second control to make a maximum deceleration when moving the FOUP to the front end side greater than a maximum deceleration when moving to the back end side, a third control to make the absolute value of the maximum deceleration when moving the FOUP to the front end side greater than the absolute value of the maximum acceleration, and a fourth control to make the absolute value of the maximum acceleration when moving the FOUP to the back end side greater than the absolute value of the maximum deceleration.

Abstract: Methods and systems of prescribing navigational instructions to autonomous vehicle, aerial as well as terrestrial, are discussed. In one embodiment, mission relevant data is collected and passed to an assessment unit. The assessment unit assess data relevant to the mission, rules and authorizations. The assessment unit either approves the mission by sending mission instructions or denies the mission by sending a rejection response. A mission is an assembly of one or more navigational containers, a navigational container being a repository for navigational guidance and rule-based authorization assessment.

Abstract: A method can include sending, via a processing device, a signal to at least two of a plurality of location indicators from an autonomous vehicle in motion and transporting equipment or passengers. The method can further include receiving signals from the at least two location indicators. The method can further include determining a location of the autonomous vehicle within an indoor facility based on the received signals. The method can further include comparing the determined location to a corresponding pre-determined location. The method can further include, in response to the determined location being different than the pre-determined location, adjusting a direction of the autonomous vehicle along a predetermined path within the indoor facility.

Abstract: A method of instance segmentation in an image and a system for instance segmentation of images. The method includes identifying, with a processor, a starting pixel associated with an object in an image, the image having a plurality of rows of pixels, the starting pixel located in a row of the plurality of rows; identifying, with the processor, at least one pixel located in an adjacent row to the row in which the starting pixel is located, the at least one pixel being part of the same object as the starting pixel; iterating the previous two identification steps using the at least one identified adjacent row pixel as a start pixel for the next iteration; and connecting, with the processor, the at least one identified adjacent row pixels to form polylines representing the object.

Abstract: A method for operating an autonomously driving vehicle that is connected to a central computer unit via a communication connection for exchanging data. During the autonomous driving mode, a request to take over a driving task is emitted to a vehicle user when at least one takeover condition is fulfilled. The takeover condition is fulfilled when it is established that the communication connection to the central computer unit is disrupted on a route portion that exceeds a predetermined length and on which the vehicle is located or which the vehicle is approaching.

Abstract: The technology relates to actively looking for an assigned passenger prior to a vehicle 100 reaching a pickup location. For instance, information identifying the pickup location and client device information for authenticating the assigned passenger is received. Sensor data is received from a perception system of the vehicle identifying objects in an environment of the vehicle. When the vehicle is within a predetermined distance from the pickup location, authenticating a client device using the client device information is attempted. When the client device has been authenticated, the sensor data is used to determine whether a pedestrian is within a first threshold distance of the vehicle. When a pedestrian is determined to be within the first threshold distance of the vehicle, the vehicle is stopped prior to reaching the pickup location, to wait for the pedestrian within the first threshold distance of the vehicle to enter the vehicle.

Abstract: A method includes receiving sensor data of an environment about a robot and generating a plurality of waypoints and a plurality of edges each connecting a pair of the waypoints. The method includes receiving a target destination for the robot to navigate to and determining a route specification based on waypoints and corresponding edges for the robot to follow for navigating the robot to the target destination selected from waypoints and edges previously generated. For each waypoint, the method includes generating a goal region encompassing the corresponding waypoint and generating at least one constraint region encompassing a goal region. The at least one constraint region establishes boundaries for the robot to remain within while traversing toward the target destination. The method includes navigating the robot to the target destination by traversing the robot through each goal region while maintaining the robot within the at least one constraint region.

Abstract: Among other things, stored data is maintained indicative of potential stopping places that are currently feasible stopping places for a vehicle within a region. The potential stopping places are identified as part of static map data for the region. Current signals are received from sensors or one or more other sources current signals representing perceptions of actual conditions at one or more of the potential stopping places. The stored data is updated based on changes in the perceptions of actual conditions. The updated stored data is exposed to a process that selects a stopping place for the vehicle from among the currently feasible stopping places.

Abstract: A method of operating an autonomous cleaning robot is described. The method includes initiating a training run of the autonomous cleaning robot and receiving, at a mobile device, location data from the autonomous cleaning robot as the autonomous cleaning robot navigates an area. The method also includes presenting, on a display of the mobile device, a training map depicting portions of the area traversed by the autonomous cleaning robot during the training run and presenting, on the display of the mobile device, an interface configured to allow the training map to be stored or deleted. The method also includes initiating additional training runs to produce additional training maps and presenting a master map generated based on a plurality of stored training maps.

Abstract: An electronic apparatus is provided. The electronic apparatus includes a communicator comprising communication circuitry, a memory storing information on an artificial intelligence model, and a processor configured to: obtain a map generated based on sensing data obtained by an external electronic apparatus, simulate driving of the external electronic apparatus on the obtained map based on a plurality of parameter values and obtain driving result data for the plurality of parameter values, train the artificial intelligence model based on the plurality of parameter values and the obtained driving result data and obtain a plurality of parameter values related to driving of the external electronic apparatus, and control the communicator to transmit the plurality of obtained parameter values to the external electronic apparatus.

Abstract: A mobile robot operation method according to an aspect of the present invention includes: a step for receiving a guidance destination input; a step for generating a global path to the received guidance destination; a step for generating a left travel guideline and a right travel guideline on the left side and the right side of the generated global path; and a step for generating a local path within a travelable range between the left travel guideline and the right travel guideline. Accordingly, the robot operation method may generate a safe and optimal guidance path when providing a guidance service.

Abstract: An operating method for navigating a device in a dynamic environment is provided. The method includes building a map based on sensor data, localizing a position of the device on the map based on the sensor data, determining a first position of a moving object on the map based on the sensor data, determining a momentum of the moving object, determining a second position of the moving object on the map based on the determined momentum, and changing the position of the device based on the determined second position of the moving object and a position of at least one obstacle.

Abstract: Provided is a robot that includes: a first sensor having a first output and configured to sense state of a robot or an environment of the robot; a first hardware machine-learning accelerator coupled to the first output of the first sensor and configured to transform information sensed by the first sensor into a first latent-space representation; a second sensor having a second output and configured to sense state of the robot or the environment of the robot; a second hardware machine-learning accelerator configured to transform information sensed by the second sensor into a second latent-space representation; and a processor configured to control the robot based on both the first latent-space representation and the second latent-space representation.

Abstract: The present disclosure relates generally to identification of drivable surfaces in connection with autonomously performing various tasks at industrial work sites and, more particularly, to techniques for distinguishing drivable surfaces from non-drivable surfaces based on sensor data. A framework for the identification of drivable surfaces is provided for an autonomous machine to facilitate it to autonomously detect the presence of a drivable surface and to estimate, based on sensor data, attributes of the drivable surface such as road condition, road curvature, degree of inclination or declination, and the like. In certain embodiments, at least one camera image is processed to extract a set features from which surfaces and objects in a physical environment are identified, and to generate additional images for further processing. The additional images are combined with a 3D representation, derived from LIDAR or radar data, to generate an output representation indicating a drivable surface.

Abstract: An ADS performs processing including setting an immobilization command to “Applied” when an autonomous state has been set to an autonomous mode, when an acceleration command has a value indicating deceleration, when an actual moving direction indicates a standstill state, and when a wheel lock request is issued, setting the acceleration command to V1, and setting the acceleration command to zero when an immobilization status has been set to “11”.

Abstract: Devices, systems, and methods for remote control of autonomous vehicles are disclosed herein. A method may include receiving, by a device, first data indicative of an autonomous vehicle in a parking area, and determining, based on the first data, a location of the autonomous vehicle. The method may include determining, based on a the location, first image data including a representation of an object. The method may include generating second image data based on the first data and the first image data, and presenting the second image data. The method may include receiving an input associated with controlling operation of the autonomous vehicle, and controlling, based on the input, the operation of the autonomous vehicle.

Abstract: Described herein are methods and systems for automatically operating autonomous vehicles to accomplish a coverage task by receiving a plurality of task parameters defining a coverage task in a certain geographical area, calculating and outputting instructions for operating first autonomous vehicle(s) to cover the certain geographical area according to a first movement path computed according to operational parameters of the first autonomous vehicle with respect to the task parameters, identifying uncovered segment(s) in the certain geographical area by analyzing coverage of the certain geographical, and calculating and outputting instructions for operating second autonomous vehicle(s) to cover the uncovered segment(s) according to a second movement path computed according to operational parameters of the second autonomous vehicle. The first autonomous vehicle(s) and the second autonomous vehicle(s) are selected to optimally accomplish the coverage task.

Abstract: A smart lawnmower and system and method for use of the same are disclosed. In one embodiment of the smart lawnmower, in a real world-to-simulated world (“real-to-sim”) training phase, the smart lawnmower constructs a simulated environment corresponding to a mowing-relevant portion of a real-world environment relative to semantic information, which may include received location signalization at an antenna In a simulated world-to-real world (“sim-to-real”) mowing phase, a mowing policy is applied to control the cutting subsystem and the drive subsystem in response to the semantic information, which may include the location signalization. In each of the real-to-sim training phase and the sim-to-real mowing phase, the smart lawnmower may provide a user interface including the simulated environment. Further, in the sim-to-real mowing phase, the smart lawnmower may synchronize the real world and the simulated world.

Abstract: An agricultural mowing assembly that includes an agricultural vehicle and at least one mowing device connected to the agricultural vehicle. The at least one mowing device includes a frame and a cutter bar movably connected to the frame. The cutter bar is configured for mowing a crop material in a field. The agricultural mowing assembly also includes a cut quality detection system that includes a plurality of sensors connected to the frame and configured for sensing color variations on the field and a controller operably connected to the plurality of sensors and receiving the sensed color variations on the field from the plurality of sensors. The controller is configured for determining a cut quality of the cutter bar based upon the sensed color variations on the field.