Abstract: Embodiments herein include an automated vehicle performing for identifying vehicles and lanes in roadway by an autonomy system of an automated vehicle. The autonomy system gathers image inputs from cameras or other sensors. The autonomy system assigns index values to the driving lanes and shoulder lanes, and then assigns the index values to the vehicles. The autonomy system generates data segments from the image data, corresponding to creating segments of an image, such that a single image is segmented for portions of the image, such as segmented outputs of each lane line or segmented outputs of portions of the vehicle. The autonomy system compares the segmented portions of the image to detect that a lane contains a vehicle.

Abstract: A tension compensation system for a robotically controlled medical device can include an instrument controller configured to operatively connect to a robotically controlled medical device to provide tension to one or more actuation cables of the robotically controlled medical device. The system can include an instrument control module configured to control the instrument controller to provide a compensation tension to at least one actuation cable of the one or more actuation cables to compensate for elongation of the at least one actuation cable of the one or more actuation cables based on actuation data associated with the at least one actuation cable of the one or more actuation cables.

Abstract: A robotic system coordinates collision-free self-storage of a robot. The robotic system initiates and performs a controlled collapse of the robot into a pre-defined compact geometry that permits self-storage in a confined, compact area when not in use. The system also coordinates collision-free self-deployments of the robot into a deployed geometry suitable for performing autonomous tasks outside of the compact storage area. The system includes a collapsible robot configured to extend and retract at least one robotic arm to perform tasks above a worksurface, a powered docking station positioned below the worksurface and including a power source interface to electrically couple the collapsible robot to a power source, and control circuitry for coordinating movements of the collapsible robot—such as collision-free self-collapse, collision-free self-deployments, and collision-free ingress and egress of the robot into and out of the compact storage area.

Abstract: A pneumatic actuator that includes a plurality of elongated inflatable chambers stacked lengthwise in an array from a top-end to a bottom end, the plurality of elongated inflatable chambers defined by an inextensible body that is inextensible along one or more plane axes of the body while being flexible in other directions.

Abstract: A method of operating a modular exoskeleton system, the method comprising: monitoring for one or more actuator units being operably coupled to or removed from the modular exoskeleton system, the modular exoskeleton system comprising at least a first actuator unit configured to be operably coupled and removed from the modular exoskeleton system; determining that the first actuator unit has been operably coupled to the modular exoskeleton system; determining the first actuator unit has been associated with a first body portion of the user; determining a first new operating configuration based at least in part on the determination that the first actuator unit has been operably coupled to the modular exoskeleton system and the determination that the first actuator unit has been associated with the first body portion of the user; and setting the first new operating configuration for the modular exoskeleton system.

Abstract: A flexible workspace system with real-time sensor feedback comprises workstations, presence sensors, workstation transmitters, a mobile device, and an upstream device. The workstations are established within a predetermined area, and each workstation includes a substantially horizontal surface having an upper side and a lower side. A presence sensor is positioned at the lower side of each workstation and detects a potential occupancy proximate an underside area below the lower side. A workstation transmitter is positioned at each workstation and coupled to the presence sensor and transmits an occupancy signal based on the potential occupancy detected by the presence sensor. The mobile device is situated within the predetermined area and detects the occupancy signal transmitted by the workstation transmitter and transmits a check-in signal based on the occupancy signal.

Abstract: An end effector device and system for suction-based grasping of bagged objects that can include a body structure with a vacuum line opening and an object engagement region, the vacuum line opening being configured to couple at least one pressure line of a vacuum pressure system to a defined internal channel of the body structure; the body structure comprising an internal structure that defines a concave inner chamber with a chamber opening at the object engagement region; and the internal structure comprising an array of inlets positioned along at least one wall of the concave inner chamber, wherein each inlet defines an opening in the body to the defined internal channel.

Abstract: An end effector for a minimally invasive medical device can include a base configured to attach to a distal end of a shaft, and a disposable distal portion configured to removably attach to the base to be disposed of after use.

Abstract: Methods and systems are described herein for determining three-dimensional locations of objects within identified portions of images. An image processing system may receive an image and an identification of location within an image. The image may be input into a machine learning model to detect one or more objects within the identified location. Multiple images may then be used to generate location estimations of those objects. Based on the location estimations, an accurate three-dimensional location may be calculated.

Abstract: The foodstuff assembly system can include: a robot arm, a frame, a set of foodstuff bins, a sensor suite, a set of food utensils, and a computing system. The system can optionally include: a container management system, a human machine interface (HMI). However, the foodstuff assembly system 100 can additionally or alternatively include any other suitable set of components. The system functions to enable picking of foodstuff from a set of foodstuff bins and placement into a container (such as a bowl, tray, or other foodstuff receptacle). Additionally or alternatively, the system can function to facilitate transferal of bulk material (e.g., bulk foodstuff) into containers, such as containers moving along a conveyor line.

Abstract: An end effector device and system for suction-based grasping of bagged objects that can include a body structure with a vacuum line opening and an object engagement region, the vacuum line opening being configured to couple at least one pressure line of a vacuum pressure system to a defined internal channel of the body structure; the body structure comprising an internal structure that defines a concave inner chamber with a chamber opening at the object engagement region; and the internal structure comprising an array of inlets positioned along at least one wall of the concave inner chamber, wherein each inlet defines an opening in the body to the defined internal channel. The body structure may additionally include a suction cup system that comprises a flexible sealing lip at the object engagement region; wherein the chamber opening being positioned within a grasping region of the sealing lip.

Abstract: A method and system having instructions to perform actions include obtaining images of an agricultural environment including a first image comprising at least one background portion and one or more regions of interest, implementing a machine learning (ML) algorithm on a portion of the first image including a portion of the background portion and the one or more regions of interest, detecting a plurality of objects associated with a plurality of real-world objects in the agricultural environment in at least one region of interest in the one or more regions of interest of the first image including detecting a first object and detecting a second object, implementing a second algorithm on the portion of the first image comprising the first object to detect one or more divided features of the first object, tracking a feature of the one or more divided features across subsequent images as the moving platform traverses the agricultural environment, tracking the second object, and selecting a target action configured

Abstract: An apparatus includes a base and a support including a non-straight channel extending therethrough. An elongated medical device extends through the channel and imparts a first load to a channel wall causing a reaction load on the support. A sensor is configured to measure a reaction load applied to the support.

Abstract: A robot in accordance with at least some embodiments of the present technology includes a torso having a superior portion, an inferior portion, and an intermediate portion therebetween. The robot further includes two legs connected to the torso via the inferior portion of the torso, two arms connected to the torso via the superior portion of the torso, and a protrusion also connected to the torso via the inferior portion of the torso and extending anteriorly from the torso. The robot is configured to move an object toward the torso at least partially via contact between the object and at least one of the arms. The robot is further configured to support a weight of the object at least partially via the protrusion while the robot ambulates via the legs.

Abstract: A method can include: receiving imaging data; identifying containers using an object detector; scheduling insertion based on the identified containers; and optionally performing an action based on a scheduled insertion. However, the method can additionally or alternatively include any other suitable elements. The method functions to schedule insertion for a robotic system (e.g., ingredient insertion of a robotic foodstuff assembly module). Additionally or alternatively, the method can function to facilitate execution of a dynamic insertion strategy; and/or facilitate independent operation of a plurality of robotic assembly modules along a conveyor line.

Abstract: One variation of a method for tracking placement of products in a store includes: accessing an image recorded by a mobile robotic system within a store; detecting a shelf in a region of the image; based on an address of the shelf, retrieving a list of products assigned to the shelf by a planogram of the store; retrieving a set of template images—from a database of template images—defining visual features of products specified in the list of products; extracting a set of features from the region of the image; determining that a unit of the product is mis-stocked on the shelf in response to deviation between the set of features and features in a template image, in the set of template images, representing the product; and in response to determining that the unit of the product is mis-stocked on the shelf, generating a restocking prompt for the product.

Abstract: Systems and methods for monitoring a sensor network are described. The system includes multiple sensors and an upstream device, and the sensors are paired in turn as transmitting and receiving sensors. The sensors collecting signal strength data for each sensor pair corresponding to beacons transmitted and received by the sensors. The upstream device generates an aggregate fingerprint based on the signal strength data, generates a zone fingerprint for each zone based on the aggregate fingerprint, and determines a wireless communication performance of the sensor network based on the zone fingerprints. The aggregate fingerprint includes a signal strength value for each sensor pair. Each zone fingerprint includes the signal strength value for each sensor pair of the corresponding zone. A sensor network configuration is changed for one or more zones based on the wireless communication performance of the sensor network.

Abstract: A real-time location system comprises sensors and an upstream device communicating with the sensors. Sensor pairs of the sensors include a transmitting sensor and a receiving sensor. Each sensor is assigned as the transmitting sensor in turn, while all other sensors are designated as the receiving sensors and collect signal strength data. The upstream device determines a labelled dataset based on the signal strength data for the sensor pairs and zone labels associated with the signal strength data. The RTLS ML model is trained based on the labelled dataset.

Abstract: An example system includes an apparatus having a first elongated medical device and a second elongated medical device; and a controller coupled to the apparatus. The controller is provided to determine a magnitude and a direction of linear translation of the first elongated medical device and responsive to the determined translation of the first elongated medical device, cause a linear translation of the second elongated medical device, the linear translation of the second elongated device having a substantially equal magnitude to the linear translation of the first elongated medical device and being in a direction opposite the direction of translation of the first elongated medical device. The controller is further provided to modify at least one parameter of the linear translation of either (a) the first elongated medical device or (b) the second elongated medical device in response to the determined translation of the first elongated device.