The present invention provides a method for automatic obstacle avoidance of a robot, and this method comprises: according to a depth sensor, obtaining depth data of movable areas of a scene in which the robot lies in; according to a preset depth threshold value, binarizing the depth data; according to an average value or a sum value of binarization processing result of areas, identifying an area where the robot is farther away from an obstacle as a moving direction of the robot. In the present invention, since the depth data is collected, no measurement dead zone is prone to occur; moreover, calculating the average value or the sum value of the binarized depth data only needs to perform a simple comparison, the processing is simpler, the processing speed is fast, and the requirement of the system and the cost are lower.

A double-threshold mechanism is used for implementing the follow-me function of a mobile robot. Initially, a user comes to a mobile robot and turns on its follow-me function. Then, the mobile robot is in the follow-me mode or can simply be described as following the user. When the user moves away from the robot, the robot determines whether the distance between itself and the user exceeds a first distance threshold. If so, the robot starts moving to follow the user. Otherwise, the robot stays put. While following the user's movement, the robot continues to monitor the distance between itself and the user. When the robot determines that the distance between them is less than a second distance threshold—because the user has slowed down or stopped, for example—the robot stops moving. The second distance threshold is lower than the first distance threshold.

Robotic systems can be capable of collision detection and avoidance. A medical robotic system can include a first kinematic chain and one or more sensors positioned to detect one or more parameters of contact with one or more portions of the first kinematic chain. The medical robotic system can be configured to cause adjustment of a configuration of the first kinematic chain from a first configuration to a second configuration based on a constraint determined from the one or more parameters of contact with the first kinematic chain detected by the one or more sensors.

Systems and methods for object guidance and collision avoidance are provided. One system includes a location sensor disposed on a movable crane. The system also includes a plurality of sensors disposed on a plurality of objects within a facility. The system further includes a controller having a receiver for monitoring signals transmitted from the location sensor disposed on a movable crane and the plurality of sensors disposed on a plurality of objects within the facility. The controller is configured to generate a travel path for the movable crane to move an object coupled with the movable crane based on the one or more intersection regions and generate an output signal to an alarm device to provide an alert, when at least one object of the plurality of objects is within a predetermined proximity of at least the object being moved by the crane.

The disclosure relates to systems and methods for determining and adjusting an allowable maximum speed of a machine for movement in a workspace. One or more sensors monitoring the workspace are arranged to obtain a three-dimensional view of the workspace. Raw data from each of the sensors is acquired and analyzed to determine the positioning and spatial relationship between the human and machine as both move throughout the workspace. This captured data is analyzed to determine a safety protocol that includes a maximum allowable speed for each of various axes of movements for the machine, wherein the safety protocol decreases the maximum allowable speed of the machine only along the one or more axes of movement where the movement of the machine approaches the human.

A control system comprises one or more processors. The one or more processors are configured to extract a feature of a person in an image captured by a camera, classify the person into a preset first group or a preset second group based on the feature, estimate a moving speed of the person belonging to the second group, and switch, based on the moving speed, a mode between a high-load mode for performing a high-load process and a low-load mode for performing a process with a load lower than a load in the high-load mode.

An apparatus for automated collision avoidance includes a sensor configured to detect an object of interest, predicting a representation of the object of interest at a future point in time, calculating an indication of a possibility of a collision with the object of interest based on the representation of the object of interest at the future point in time, and executing a collision avoidance action based on the indication.

A robot system for human-robot collaboration is disclosed that includes one or more proximity sensing elements disposed on the movable parts of the robot, joint position sensing sensors, and a safety control module connects the proximity sensing element and joint position sensing sensors and monitors the speed of the robot and the proximity distance to the objects and stop the robot safely when speed exceed the set limit. The safety control module switches the safety status of the robot when a set proximity distance threshold is triggered. Then, multiple embodiments of the safety status triggered by proximity sensing are introduced for different processes of the human-robot collaboration, includes separation monitoring, force limiting for bumping, and manipulation of the robot. Furthermore, embodiments of utilizing different types of sensors to implement the proximity sensing elements are also disclosed.

The material contained in this disclosure pertains to robotics related to convertible robots incorporating telecommunication elements. Embodiments of the system and apparatuses described can facilitate instant communication with family and friends, health status monitoring and support from caregivers; and promote optimal health, longevity, and independent living by providing high-tech economical solutions at each stage of the aging process. Embodiments of the system and apparatuses may be converted from an independent telecommunications robot, to a robotic walker, to a robotic wheelchair.

A computer-implemented method for determining a control trajectory for a robotic device. The method includes: performing an information theoretic model predictive control applying a control trajectory sample prior in each time step to obtain a control trajectory for a given time horizon; determining the control trajectory sample prior depending on a data-driven trajectory prediction model which is trained to output a control trajectory sample as the control trajectory sample prior based on an actual state of the robotic device.