Abstract: An autonomous, mobile robotic device (AMR) is configured with one or more UVC radiation sources, and operates to traverse a path while disinfecting an interior space. Each UVC radiation source is connected to the AMR by an articulating arm that is controlled to orient each source towards a feature or surface that is selected for disinfection during the time that the AMR is moving through the space. The location of each feature selected for disinfection can be mapped, and this map information, a current AMR location and pose can be used to generate signals that are used to control the articulating arm to orient each UVC lamp towards a feature that is selected for disinfection.

Abstract: An autonomous, mobile robotic device (AMR) is configured with one or more UVC radiation sources, and operates to traverse a path while disinfecting an interior space. Each UVC radiation source is connected to the AMR by an articulating arm that is controlled to orient each source towards a feature or surface that is selected for disinfection during the time that the AMR is moving through the space. The location of each feature selected for disinfection can be mapped, and this map information, a current AMR location and pose can be used to generate signals that are used to control the articulating arm to orient each UVC lamp towards a feature that is selected for disinfection.

Abstract: Understanding the intent of human drivers and adapting to their driving styles is used to increased efficiency and safety of autonomous vehicles (AVs) by enabling them to behave in safe and predictable ways without requiring explicit inter-vehicle communication. A Social Value Orientation (SVO), which quantifies the degree of an agent's selfishness or altruism, is estimated by the AV for other vehicles to better predict how they will interact and cooperate with others. Interactions between agents are modeled as a best response game wherein each agent negotiates to maximize their own utility. A dynamic game solution uses the Nash equilibrium, yielding an online method of predicting multi-agent interactions given their SVOs. This approach allows autonomous vehicles to observe human drivers, estimate their SVOs, and generate an autonomous control policy in real time.

Abstract: An approach to autonomous navigation of a vehicle augments a static map of an environment with a clutter map characterizing a risk of encountering an object that is not represented in the static map of the environment. For example, the clutter map may be based on locations and velocities of those objects, and route planning may avoid planning a path through locations that have a high risk of occupancy, and therefore potential delay or collision.

Abstract: Systems and methods described herein relate to estimating risk associated with a vehicular maneuver. One embodiment acquires a geometric representation of an intersection including a lane in which a vehicle is traveling and at least one other lane; discretizes the at least one other lane into a plurality of segments; determines a trajectory along which the vehicle will travel; estimates a probability density function for whether a road agent external to the vehicle is present in the respective segments; estimates a traffic-conflict probability of a traffic conflict in the respective segments conditioned on whether an external road agent is present; estimates a risk associated with the vehicle following the trajectory by integrating a product of the probability density function and the traffic-conflict probability over the at least one other lane and the plurality of segments; and controls operation of the vehicle based, at least in part, on the estimated risk.

Abstract: An autonomous, mobile robotic device (AMR) is configured with one or more UVC radiation sources, and operates to traverse a path while disinfecting an interior space. Each UVC radiation source is connected to the AMR by an articulating arm that is controlled to orient each source towards a feature or surface that is selected for disinfection during the time that the AMR is moving through the space. The location of each feature selected for disinfection can be mapped, and this map information, a current AMR location and pose can be used to generate signals that are used to control the articulating arm to orient each UVC lamp towards a feature that is selected for disinfection.

Abstract: An autonomous, mobile robotic device (AMR) is configured with one or more UVC radiation sources, and operates to traverse a path while disinfecting an interior space. Each UVC radiation source is connected to the AMR by an articulating arm that is controlled to orient each source towards a feature or surface that is selected for disinfection during the time that the AMR is moving through the space. The location of each feature selected for disinfection can be mapped, and this map information, a current AMR location and pose can be used to generate signals that are used to control the articulating arm to orient each UVC lamp towards a feature that is selected for disinfection.

Abstract: An autonomous, mobile robotic device (AMR) is configured with one or more UVC radiation sources, and operates to traverse a path while disinfecting an interior space. Each UVC radiation source is connected to the AMR by an articulating arm that is controlled to orient each source towards a feature or surface that is selected for disinfection during the time that the AMR is moving through the space. The location of each feature selected for disinfection can be mapped, and this map information, a current AMR location and pose can be used to generate signals that are used to control the articulating arm to orient each UVC lamp towards a feature that is selected for disinfection.

Abstract: A method is disclosed for use in a planning agent, the method including: identifying a first agent in a vicinity of the planning agent; identifying a location of the first agent and a velocity of the first agent; calculating a set of occupancy costs for the first agent, each occupancy cost in the set of occupancy costs being associated with a different respective location in the vicinity of the planning agent, each occupancy cost in the set of occupancy costs being calculated at least in part based on a cost function that depends on the location of the first agent and the velocity of the first agent; and changing at least one of speed or direction of travel of the planning agent based on the set of occupancy costs.

Abstract: Understanding the intent of human drivers and adapting to their driving styles is used to increased efficiency and safety of autonomous vehicles (AVs) by enabling them to behave in safe and predictable ways without requiring explicit inter-vehicle communication. A Social Value Orientation (SVO), which quantifies the degree of an agent's selfishness or altruism, is estimated by the AV for other vehicles to better predict how they will interact and cooperate with others. Interactions between agents are modeled as a best response game wherein each agent negotiates to maximize their own utility. A dynamic game solution uses the Nash equilibrium, yielding an online method of predicting multi-agent interactions given their SVOs. This approach allows autonomous vehicles to observe human drivers, estimate their SVOs, and generate an autonomous control policy in real time.

Abstract: An approach to autonomous navigation of a vehicle augments a static map of an environment with a clutter map characterizing a risk of encountering an object that is not represented in the static map of the environment. For example, the clutter map may be based on locations and velocities of those objects, and route planning may avoid planning a path through locations that have a high risk of occupancy, and therefore potential delay or collision.

Abstract: Systems and methods described herein relate to estimating risk associated with a vehicular maneuver. One embodiment acquires a geometric representation of an intersection including a lane in which a vehicle is traveling and at least one other lane; discretizes the at least one other lane into a plurality of segments; determines a trajectory along which the vehicle will travel; estimates a probability density function for whether a road agent external to the vehicle is present in the respective segments; estimates a traffic-conflict probability of a traffic conflict in the respective segments conditioned on whether an external road agent is present; estimates a risk associated with the vehicle following the trajectory by integrating a product of the probability density function and the traffic-conflict probability over the at least one other lane and the plurality of segments; and controls operation of the vehicle based, at least in part, on the estimated risk.

Abstract: A method is disclosed for use in a planning agent, the method including: identifying a first agent in a vicinity of the planning agent; identifying a location of the first agent and a velocity of the first agent; calculating a set of occupancy costs for the first agent, each occupancy cost in the set of occupancy costs being associated with a different respective location in the vicinity of the planning agent, each occupancy cost in the set of occupancy costs being calculated at least in part based on a cost function that depends on the location of the first agent and the velocity of the first agent; and changing at least one of speed or direction of travel of the planning agent based on the set of occupancy costs.