Abstract: A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.

Abstract: Techniques for autonomously establishing, maintaining, and repairing of a wireless communication network among multiple autonomous mobile nodes (AMN) are provided. The multiple AMNs are flown towards a first node. A tentacle is established with the first node and extended to cover a second node over a distance, thereby establishing a wireless communication network between the first node and the second node via the multiple AMNs. Any damage to the established wireless communication network or tentacle may be autonomously detected and repaired by using spare AMNs. Further, the communication network may be used to enable autonomous detection, tracking of the second node, as well as autonomous detection of a contamination area, based on data received from one or more sensors onboard the AMNs deployed in the air.

Abstract: A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.

Abstract: A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.

Abstract: Techniques for autonomously establishing, maintaining, and repairing of a wireless communication network among multiple autonomous mobile nodes (AMN) are provided. The multiple AMNs are flown towards a first node. A tentacle is established with the first node and extended to cover a second node over a distance, thereby establishing a wireless communication network between the first node and the second node via the multiple AMNs. Any damage to the established wireless communication network or tentacle may be autonomously detected and repaired by using spare AMNs. Further, the communication network may be used to enable autonomous detection, tracking of the second node, as well as autonomous detection of a contamination area, based on data received from one or more sensors onboard the AMNs deployed in the air.

Abstract: Techniques for autonomously establishing, maintaining, and repairing of a wireless communication network among multiple autonomous mobile nodes (AMN) are provided. The multiple AMNs are flown towards a first node. A tentacle is established with the first node and extended to cover a second node over a distance, thereby establishing a wireless communication network between the first node and the second node via the multiple AMNs. Any damage to the established wireless communication network or tentacle may be autonomously detected and repaired by using spare AMNs. Further, the communication network may be used to enable autonomous detection, tracking of the second node, as well as autonomous detection of a contamination area, based on data received from one or more sensors onboard the AMNs deployed in the air.

Abstract: A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.

Abstract: A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.

Abstract: Techniques for autonomously establishing, maintaining, and repairing of a wireless communication network among multiple autonomous mobile nodes (AMN) are provided. The multiple AMNs are flown towards a first node. A tentacle is established with the first node and extended to cover a second node over a distance, thereby establishing a wireless communication network between the first node and the second node via the multiple AMNs. Any damage to the established wireless communication network or tentacle may be autonomously detected and repaired by using spare AMNs. Further, the communication network may be used to enable autonomous detection, tracking of the second node, as well as autonomous detection of a contamination area, based on data received from one or more sensors onboard the AMNs deployed in the air.

Abstract: A method and apparatus are provided for autonomously detecting and reporting anomalies in actions of an autonomous mobile node, or in behaviors of a swarm of autonomous mobile nodes to an operator. The autonomous mobile node may experience anomalies or unexpected situations due to various failures or external influence (e.g. natural weather phenomena, enemy threats). During a training phase a prediction model and a structured model may be established from measurement data received from one or more sensors of an autonomous mobile node or a swarm of nodes while executing an action or behavior under normal circumstances. A prediction model forecasts the expected outcome of an action or behavior, and structured model helps quantify the similarity of a learned action or behavior to the currently observed situation. Based on the measurement data applicable models can be used for an action or behavior for anomaly detection in the action or behavior.

Abstract: Designs and techniques for fluid thrusters and vehicles that are powered by propelling fluids with fluid thrusters. Multiplex-thruster (MT) systems are disclosed that include a single thruster and a flow multiplexer with multiple channels to deliver thrusting flow in various directions.

Abstract: Designs of single-end-operative reconfigurable genderless connectors that include a base, a plurality of movable jaws that are formed on the base and can engage to the jaws of another connector, and an actuator that is mounted on the base and can engage and move the jaws of the reconfigurable connector to connect the reconfigurable connector with another connector.

Abstract: Designs and techniques for fluid thrusters and vehicles that are powered by propelling fluids with fluid thrusters. Multiplex-thruster (MT) systems are disclosed that include a single thruster and a flow multiplexer with multiple channels to deliver thrusting flow in various directions.

Abstract: Designs and techniques for fluid thrusters and vehicles that are powered by propelling fluids with fluid thrusters. Multiplex-thruster (MT) systems are disclosed that include a single thruster and a flow multiplexer with multiple channels to deliver thrusting flow in various directions.

Abstract: Designs and techniques for fluid thrusters and vehicles that are powered by propelling fluids with fluid thrusters. Multiplex-thruster (MT) systems are disclosed that include a single thruster and a flow multiplexer with multiple channels to deliver thrusting flow in various directions.

Abstract: Systems and techniques are described for distributed control and coordination of autonomous agents in a system. A protocol for distributed control allows autonomous agents to negotiate a group task for the agents, such as locomotion or self-reconfiguration in a robot application, and to synchronize individual agent actions to effect the group task. A protocol for adaptive communication allows autonomous agents, such as physically coupled self-sufficient robot modules, to continuously discover changes in their local topology. In general, in one implementation, the technique includes: discovering a local topology, which includes a type of a communication connection to autonomous agents in the reconfigurable network topology, and determining an action based upon a received control message and the determined local topology.