5164results about "Autonomous decision making process" patented technology

A system for controlling more than one remote vehicle. The system comprises an operator control unit allowing an operator to receive information from the remote vehicles and send commands to the remote vehicles via a touch-screen interface, the remote vehicles being capable of performing autonomous behaviors using information received from at least one sensor on each remote vehicle. The operator control unit sends commands to the remote vehicles to perform autonomous behaviors in a cooperative effort, such that high-level mission commands entered by the operator cause the remote vehicles to perform more than one autonomous behavior sequentially or concurrently. The system may perform a method for generating obstacle detection information from image data received from one of a time-of-flight sensor and a stereo vision camera sensor.

A method and system for piece-picking or piece put-away within a logistics facility. The system includes a central server and at least one mobile manipulation robot. The central server is configured to communicate with the robots to send and receive piece-picking data which includes a unique identification for each piece to be picked, a location within the logistics facility of the pieces to be picked, and a route for the robot to take within the logistics facility. The robots can then autonomously navigate and position themselves within the logistics facility by recognition of landmarks by at least one of a plurality of sensors. The sensors also provide signals related to detection, identification, and location of a piece to be picked or put-away, and processors on the robots analyze the sensor information to generate movements of a unique articulated arm and end effector on the robot to pick or put-away the piece.

The present invention relates to a helicopter having a modular airframe, with multiple layers which can be connected easily, the layers which house the electronics (autopilot and navigation systems), batteries, and payload (including camera system) of the helicopter. The helicopter has four, six, and eight rotors, which can be easily changed via removing one module of the airframe. In one embodiment, the airframe has a vertical stacked appearance, and in another embodiment, a domed shape (where several of the layers are stacked internally). In one embodiment, there is a combination landing gear and camera mount. The helicopter allows for simple flight and usage by remote control, and non-remote control, users.

Embodiments, systems, and techniques for vehicle operation assistance are provided herein. Vehicle operation assistance may be provided by monitoring characteristics of an occupant of a vehicle and determining an emergency status for the occupant based on characteristics of the occupant, transmitting a request for help based on the emergency status indicating the occupant of the vehicle is experiencing an emergency, receiving a “follow me” request from a potential leader vehicle, enabling follower mode such that vehicle is a follower vehicle and the potential leader vehicle is a leader vehicle, establishing a connection with the leader vehicle and receiving navigation instructions from the leader vehicle based on the vehicle being in follower mode, generating driving action commands based on navigation instructions, and executing respective driving action commands in an autonomous fashion based on the vehicle being in follower mode.

A collaborative engagement system comprises: at least two unmanned vehicles comprising an unmanned air vehicle including sensors configured to locate a target and an unmanned ground vehicle including sensors configured to locate and track a target; and a controller facilitating control of, and communication and exchange of data to and among the unmanned vehicles, the controller facilitating data exchange via a common protocol. The collaborative engagement system controls the unmanned vehicles to maintain line-of-sight between a predetermined target and at least one of the unmanned vehicles.

System and method for behavior based control of an autonomous vehicle. Actuators (e.g., linkages) manipulate input devices (e.g., articulation controls and drive controls, such as a throttle lever, steering gear, tie rods, throttle, brake, accelerator, or transmission shifter) to direct the operation of the vehicle. Behaviors that characterize the operational mode of the vehicle are associated with the actuators. The behaviors include action sets ranked by priority, and the action sets include alternative actions that the vehicle can take to accomplish its task. The alternative actions are ranked by preference, and an arbiter selects the action to be performed and, optionally, modified.

A robot includes a hazard sensor, a locomotor, and a system controller. The robot senses a hazard intensity at a location of the robot, moves to a new location in response to the hazard intensity, and autonomously repeats the sensing and moving to determine multiple hazard levels at multiple locations. The robot may also include a communicator to communicate the multiple hazard levels to a remote controller. The remote controller includes a communicator for sending user commands to the robot and receiving the hazard levels from the robot. A graphical user interface displays an environment map of the environment proximate the robot and a scale for indicating a hazard intensity. A hazard indicator corresponds to a robot position in the environment map and graphically indicates the hazard intensity at the robot position relative to the scale.

Methods for personalized driving of autonomously driven vehicles include: (a) downloading at least a portion of a driving profile to a vehicle, wherein the vehicle is configured for autonomous driving and wherein the driving profile is associated with a specific driver; and (b) executing one or a plurality of operating instructions prescribed by the driving profile, such that the vehicle is operable in a driving style imitative of the specific driver. Apparatuses for personalized driving of autonomously driven vehicles are described.

A transport arrangement system operates to receive a transport request from a user, and to make a selection of a vehicle type for the user based at least in part on a set of criteria associated with the transport request or user information. For example, the determination of whether an autonomous vehicle is to be provided can be based at least in part on the destination specified with the transport request.

A method of establishing an area of confinement and an autonomous robot for performing a task within the area of confinement. In one aspect, the invention can be a method of defining an area of confinement for an autonomous robot comprising: a) positioning the autonomous robot at a first location point P₁, the autonomous robot comprising a location tracking unit, and recording the first location point P₁ within a memory device; b) moving the autonomous robot from the first location point P₁ to a plurality of location points P_2-N and recording each of the plurality of location points P_2-N within the memory device; and c) defining, with a central processing unit, a first closed-geometry comprising the first location point P₁ and the plurality of location points P_2-N as a perimeter of the area of confinement within the memory device.

Systems, methods, and user interfaces are used for controlling a robot. An environment map and a robot designator are presented to a user. The user may place, move, and modify task designators on the environment map. The task designators indicate a position in the environment map and indicate a task for the robot to achieve. A control intermediary links task designators with robot instructions issued to the robot. The control intermediary analyzes a relative position between the task designators and the robot. The control intermediary uses the analysis to determine a task-oriented autonomy level for the robot and communicates target achievement information to the robot. The target achievement information may include instructions for directly guiding the robot if the autonomy level indicates low robot initiative and may include instructions for directing the robot to determine a robot plan for achieving the task if the autonomy level indicates high robot initiative.

Systems and methods for switching between autonomous and manual operation of a vehicle are described. In one embodiment, there is a mechanical control system that receives manual inputs from a mechanical operation member to operate the vehicle in manual mode. There is further an actuator that receives autonomous control signals generated by a controller. When the actuator is engaged, it operates the vehicle in an autonomous mode, and when disengaged, it operates the vehicle in manual mode. In another embodiment, there is an E-Stop system to disengage systems that cause the vehicle to move, such as the engine, while still leaving power in the systems that do not cause the vehicle to move. There is a method for autonomous mode starting of a vehicle, comprising receiving a signal indicating autonomous mode, determining that a parking brake lever is set and the brakes are engaged, disengaging the brakes while maintaining the lever in the set position, and engaging in autonomous mode. There is a safety system with a mechanical bias to suppress moveable systems of the vehicle, comprising a clutch that releases the mechanical bias to permit movement of the moveable system when the clutch is engaged. In another embodiment a system comprises a mechanical linkage with a restoration member that permits control of an operation system of the vehicle by a remote operation member when the restoration member is engaged. There is also an actuator that prohibits control of the operation system by the remote operation member when the actuator is engaged.

An autonomous vehicle and systems having an interface for payloads that allows integration of various payloads with relative ease. There is a vehicle control system for controlling an autonomous vehicle, receiving data, and transmitting a control signal on at least one network. A payload is adapted to detachably connect to the autonomous vehicle, the payload comprising a network interface configured to receive the control signal from the vehicle control system over the at least one network. The vehicle control system may encapsulate payload data and transmit the payload data over the at least one network, including Ethernet or CAN networks. The payload may be a laser scanner, a radio, a chemical detection system, or a Global Positioning System unit. In certain embodiments, the payload is a camera mast unit, where the camera communicates with the autonomous vehicle control system to detect and avoid obstacles. The camera mast unit may be interchangeable, and may include structures for receiving additional payload components.

A legged vehicle includes a body, wherein the body includes a major axis corresponding to a primary direction of travel; a plurality of leg mechanisms attached to the body, wherein each leg is attached at its proximal end at one or more discrete attachment points, wherein the attachment points are arranged in-line, one behind the other, with respect to the body, each of the legs including actuators attached between the legs and the body and between adjacent leg members, said legs being actuated for movement of a distal end in three dimensions; a control system in communication with the leg mechanisms to coordinate movements of the leg mechanisms according to approximately single track foot placement, and movement of the legged vehicle in three dimensions over the ground; and a power source connected to and driving the control system components and the plurality of actuators and joints which drive the legs.

A system for allowing an operator to switch between remote vehicle tele-operation and one or more remote vehicle autonomous behaviors. The system comprises: an operator control unit receiving input from the operator including instructions for the remote vehicle to execute an autonomous behavior; a control system on the remote vehicle for receiving the instruction to execute an autonomous behavior from the operator control unit; and a GPS receiver, an inertial measurement unit, and a navigation CPU on the remote vehicle. Upon receiving the instruction to execute an autonomous behavior, the remote vehicle executes that autonomous behavior using input from the GPS receiver, the inertial measurement unit (IMU), and the navigation CPU.

An automated distribution center includes an array with storage locations arranged along aisle(s) having a floor, and a mezzanine platform above the floor, the floor and mezzanine being configured for human picker access to the storage locations, an automated guided vehicle (AGV) configured for traverse of the floor and mezzanine to the storage locations, and for transporting a storage container to and from the storage locations, the floor and mezzanine each having an undeterministic traverse surface for the AGV, the AGV is configured so that the surface provides holonomic selectable paths for the AGV substantially everywhere on the surface, each path being selectable by the AGV, and an order filling station, where one or more goods are picked from container(s) to fill order(s), wherein the AGV is configured to pick the container from a storage location and transport the container on the surface between the storage array and the station.

The present invention provides systems, methods, and devices related to target tracking by UAVs. The UAV may be configured to receive target information from a control terminal related to a target to be tracked by an imaging device coupled to the UAV. The target information may be used by the UAV to automatically track the target so as to maintain predetermined position and/or size of the target within one or more images captured by the imaging device. The control terminal may be configured to display images from the imaging device as well as allowing user input related to the target information.

A system may include a user interface, a transmitter, a processor, and a memory having a program communicatively connected to the processor. The processor may be configured to receive a body sensor output associated with an occupant of a vehicle, receive a vehicle sensor output associated with the vehicle, compare the body and vehicle sensor outputs with a threshold, prompt for a confirmation associated with at least one of the body and vehicle sensor outputs, determine an issue type based on at least one of the body and vehicle sensor outputs, and send a notification including the issue type.

In an autonomous driving system in which a plurality of autonomous driving vehicles drive under the control by occlusion control, such a situation is prevented that a vehicle is disabled to drive by a failure of an external world sensor for recognizing an obstacle and stops in an occlusion region thereby to obstruct advancement of overall succeeding vehicles to remarkably degrade the efficiency of the overall transportation work. In the autonomous driving system of the present invention, an autonomous driving vehicle which detects an obstacle or a driving road by a sensor and performs autonomous driving includes sensor state evaluation means configured to evaluate a state of performance degradation of the sensor, speed and steering angle control value setting means configured to provide limit values to the driving speed and the steering angle based on a state of performance degradation of the sensor, and movement obstacle evaluation means configured to evaluate an influence on movement of other vehicles when the vehicle stops at a position at present. When the sensor suffers from performance degradation, the vehicle stops after it drives within the set limit values to the speed and the steering angle to a point at which the vehicle does not obstruct movement of other vehicles.

Embodiments of the invention provide systems and methods for obstacle avoidance. In some embodiments, a robotically controlled vehicle capable of operating in one or more modes may be provided. Examples of such modes include teleoperation, waypoint navigation, follow, and manual mode. The vehicle may include an obstacle detection and avoidance system capable of being implemented with one or more of the vehicle modes. A control system may be provided to operate and control the vehicle in the one or more modes. The control system may include a robotic control unit and a vehicle control unit.

Systems and methods for efficiently addressing technical and privacy/authorization obstacles associated with tracking of individuals in a vehicle, and enabling route-based analysis to determine driving behavior, socio-demographics, future profitability, and interests of individuals or self-driving systems. Driving information is collected using a device associated with a driver and a vehicle or using data collected by systems of self-driving vehicles. The frequency and methods used for the collection of driving information can be modified based on location and movement of the device and based on previous classification of the driver or self-driving system, thereby enabling efficient use of bandwidth and battery and increasing accuracy of the classification. The driving information is encoded and transmitted to a server, where future typical route segments that the driver is likely to travel are predicted, and the driver, or the self-driving system, is classified into one or more groups based on the encoded driving information.

Various types and levels of operator assistance are performed within a unified, configurable framework. A model of the device with a model of the environment and the current state of the device and the environment are used to iteratively generate a sequence of optimal device control inputs that, when applied to a model of the device, generate an optimal device trajectory through a constraint-bounded corridor or region within the state space. This optimal trajectory and the sequence of device control inputs that generates it is used to generate a threat assessment metric. An appropriate type and level of operator assistance is generated based on this threat assessment. Operator assistance modes include warnings, decision support, operator feedback, vehicle stability control, and autonomous or semi-autonomous hazard avoidance. The responses generated by each assistance mode are mutually consistent because they are generated using the same optimal trajectory.

A method for enhancing operational efficiency of a remote vehicle using a diagnostic behavior. The method comprises inputting and analyzing data received from a plurality of sensors to determine the existence of deviations from normal operation of the remote vehicle, updating parameters in a reference mobility model based on deviations from normal operation, and revising strategies to achieve an operational goal of the remote vehicle to accommodate deviations from normal operation. An embedded simulation and training system for a remote vehicle. The system comprises a software architecture installed on the operator control unit and including software routines and drivers capable of carrying out mission simulations and training.

A control apparatus of a vehicle is provided. In the control apparatus, an unable-to-drive state of the driver of the vehicle is detected or determined. The unable-to-drive state is a state where the driver is unable to drive the vehicle. When the emergency that the driver has become the unable-to-drive state is detected or determined, the detection or determination result is notified to the outside. A leading vehicle which is adapted to leading the vehicle based on the notification, is recognized. Automatic follow-up running control is performed wherein the vehicle is made to automatically follow the leading vehicle.

A behavior controlling apparatus by which the mobility area of a robot apparatus may be controlled in a simplified manner using plural landmarks. A landmark recognition unit 410 uniquely recognizes the landmarks to acquire the landmark position information rPo(x,y,z). A landmark map building unit 420 integrates the totality of the landmark position information rPo(x,y,z) sent by the landmark recognition unit 410 to build a landmark map which has integrated the geometric topology of the landmarks. Using the landmark map information rPoxN, a mobility area recognition unit 430 builds a mobility area map representing a mobility area for the robot. Using the mobility area map, sent from the mobility area recognition unit 430, a behavior controller 440 controls the autonomous behavior of the robot apparatus 1 so that the robot apparatus 1 will not come out of or into the mobility area.

Systems, methods and apparatus may be configured to implement automatic semantic classification of a detected object(s) disposed in a region of an environment external to an autonomous vehicle. The automatic semantic classification may include analyzing over a time period, patterns in a predicted behavior of the detected object(s) to infer a semantic classification of the detected object(s). Analysis may include processing of sensor data from the autonomous vehicle to generate heat maps indicative of a location of the detected object(s) in the region during the time period. Probabilistic statistical analysis may be applied to the sensor data to determine a confidence level in the inferred semantic classification. The inferred semantic classification may be applied to the detected object(s) when the confidence level exceeds a predetermined threshold value (e.g., greater than 50%).