Intel Corporation

Yang Peng

Michael Paulitsch

Rafael Rosales

Florian Geissler

Ralf Graefe

Fabian Oboril

Rita H Wouhaybi

Ignacio Javier Alvarez

Cornelius Buerkle

Neslihan Kose Cihangir

Siew Wen Chin

Frederik Pasch

Norbert Stoeffler

Kay-ulrich Scholl

Disclosed herein are systems, devices, and methods of a robot safety system for improving the safety of human-robot collaborations. The robot safety system may include a processor that receives a collaboration policy for task collaboration between a robot and a collaborator. The task collaboration may include a movement plan of the robot to move a manipulator to a collaboration position. The robot safety system may also determine a new collaboration position based on the collaboration policy. The robot safety system may also update the collaboration position of the movement plan to the new collaboration position.

Repetitive task and contextual risk analytics for human-robot collaboration

Disclosed herein are systems, devices, and methods for efficiently checking the integrity of a robot system. The integrity-checking system may generate a predefined motion instruction for a robot, where the predefined motion instruction instructs the robot to perform a random movement at a test time. The random movement may be associated with an expected observation at the test time. The integrity-checking system may also determine a systematic failure based on a difference between the expected observation and a current observation of the robot at the test time. The current observation may be determined from received sensor data, and if the integrity-checking system detects a failure, it may stop the robot's motion or other mitigating instructions.

Integrity and safety checking for robots

Disclosed herein are systems and methods for dynamically minimizing a perceived risk for a multimodal mobility service. The systems and methods may include identifying a safety-related attribute for a route from a starting location to an ending location. The safety-related attribute may be associated with a perceived risk for a dimension of the route. A risk score for the route may be determined using the safety-related attribute. The risk score for the multimodal mobility service based on the perceived risk for the dimension of the route.

Multimodal mobility services with minimized perceived risks

Disclosed herein are systems and methods for dynamically distributing a safety, awareness task. The systems and methods may include receiving hardware resources data associated with a plurality of remote computing systems. A plurality of safety assurance profiles may be received. Each of the plurality of safety assurance profiles may be associated with a respective service. A safety assurance task may be dynamically assigned to one of the plurality of remote computing systems based on the hardware resources data and one of the plurality of safety assurance profiles.

Dynamic safety awareness task distribution

A device may include an image sensor, configured to generate image sensor data representing a vicinity of the device; an image processor, configured to generate a first code from the image sensor data using a code generation protocol; an input validity checker, configured to compare the first code to a second code; and if a similarity of the first code and the second code is within a predetermined range, operate according to a first operational mode; and if the similarity of the first code and the second code is not within the predetermined range, operate according to a second operational mode.

Sensor verifier and method

Disclosed herein is a vehicle handover system that monitors an environment of a vehicle. The vehicle handover system receives a transition request to change control of the vehicle from an automated driving mode to a passenger of the vehicle. The vehicle handover system detects a key event that may be relevant to the transition request and the detection of the key event is based on the monitored environment. The vehicle handover system may generate a handover scene that includes images associated with the key event, and the images include an image sequence over a time-period of the key event. Before the vehicle handover system changes control of the vehicle from the automated driving mode to the passenger, the handover scene is displayed to the passenger.

Handover assistant for machine to driver transitions

Described herein is a high confidence ground truth information service executing on a network of edge computing devices. A variety of participating devices obtain high confidence ground truth information relating to objects in a local environment. This information is communicated to the ground truth information service, where it may be verified and aggregated with similar information before being communicated as part of an acquired ground truth dataset to one or more subscribing devices. The subscribing devices use the ground truth information, as included in the ground truth dataset, to both validate and improve their supervised learning systems.

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Munich, Germany

Yang Peng