Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. In particular, a method may include receiving first sensor data from a first sensor disposed on a vehicle, the first sensor data associated with a first sensor modality, and receiving second sensor data from a second sensor disposed on the vehicle, the second sensor data associated with a second sensor modality different than the first sensor modality. The method may further include generating fused sensor data representing at least a portion of the first sensor data and the second sensor data, generating a trajectory for the vehicle based in part on the fused sensor data, and controlling the vehicle based in part on the trajectory.

Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. In particular, a method may include receiving first sensor data from a first sensor disposed on a vehicle, the first sensor data associated with a first sensor modality, and receiving second sensor data from a second sensor disposed on the vehicle, the second sensor data associated with a second sensor modality different than the first sensor modality. The method may further include generating fused sensor data representing at least a portion of the first sensor data and the second sensor data, generating a trajectory for the vehicle based in part on the fused sensor data, and controlling the vehicle based in part on the trajectory.

A moving body has a control unit that determines priority relating to movement on the basis of prescribed rules, the control unit comparing, on the basis of the prescribed rules, a first determination value that is the determination value for the moving body, and a second determination value that is the determination value for another moving body, whereby the priority of the moving body is determined in relation to the other moving body.

A navigation system useful for providing speed and heading and other navigational data to a drive system of a moving body, e.g., a vehicle body or a mobile robot, to navigate through a space. The navigation system integrates an inertial navigation system, e.g., a unit or system based on an inertial measurement unit (IMU). with a vision-based navigation system unit or system such that the inertial navigation system can provide real time navigation data and the vision-based navigation can provide periodic, but more accurate, navigation data that is used to correct the inertial navigation system's output. The navigation system was designed with the goal in mind of providing low effort integration of inertial and video data. The methods and devices used in the new navigation system address problems associated with high accuracy dead reckoning systems (such as a typical vision-based navigation system) and enhance performance with low cost IMUs.

Systems and methods for increasing the efficiency of vehicle platooning systems are described. In one aspect, drivers are more likely to enjoy a system if it begins platooning as desired and does not accidently end platoons. When a certain amount of data packets sent between vehicles are dropped, systems typically will either not engage in a platoon or end a current platoon. When a platoon has a very small gap between vehicles, the platoon should endor not start, when a certain amount of packets are dropped. However, if a gap is large enough to provide a driver with more time to react, a system may accept a greater amount of dropped packets before it refuses to start a platoon or causes the end of a platoon.

Provided is a method for delivering goods through an unmanned aerial vehicle group including a plurality of aircraft respectively connected to delivery target goods. The method comprises identifying, by a master aircraft of the unmanned aerial vehicle group, an actual load applied to each of the aircraft by the goods while the unmanned aerial vehicle group is flying to deliver the goods, and controlling the unmanned aerial vehicle group by the master aircraft to adjust the actual load applied to each of the aircraft.

A management device that manages a flight route of a plurality of unmanned aerial vehicles (UAVs) includes a communication unit that acquires a detection result of an obstacle by a first UAV including an obstacle detection function and an evaluating unit that generates evaluation data of the flight route for selecting a UAV to fly on the flight route based on the detection result.

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. A computing device may receive data for the same road segment from autonomous vehicles, including (i) an indication of a location within the road segment, and (ii) an indication of a condition of the road segment. The computing device may generate, from the data for the same road segment, an overall indication of the condition of the road segment, which may include a recommendation to vehicles approaching the road segment. Additionally, the computing device may receive a request from a computing device within a vehicle approaching the road segment to display vehicle data. The overall indication for the road segment may then be displayed on a user interface of the computing device.

The present disclosure relates to the field of swarm intelligence and provides a multi-intelligent-agent cooperated transportation method and system as well as a computer readable storage medium. The method includes: establishing a transportation model of a multi-intelligent-agent formation, and performing obstacle avoidance control between intelligent agents and neighbor intelligent agents based on pheromones of the intelligent agents themselves and the neighbor intelligent agents of the intelligent agents; acquiring, by a leader intelligent agent, state information of the leader intelligent agent by utilizing a distributed observer triggered based on self-pheromone release; regulating, by utilizing an intelligent agent cooperation controller triggered based on self-pheromone release, state information of the intelligent agents according to the state information of the leader intelligent agent; and enabling the neighbor intelligent agents of the intelligent agents to jump the queue to the multi-intelligent-agent formation according to the state information of the intelligent agents when obstacles are encountered.

A method for workforce management includes receiving a service request associated with a task area from a user device, and controlling movement of an unmanned aerial machine from a home base to the task area. The unmanned aerial machine acquires evaluation data about the task area. The method also includes determining a task to be performed based on the service request, the task area, and the evaluation data. Further, the method includes selecting one or more autonomous machines to perform the task based on at least the task and a location of the task area, and controlling the selected one or more autonomous machines to perform the task