Abstract: A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change. Various aspects of such robot motion planning are implemented in particular systems and methods that facilitate motion planning of the robot for various environments and tasks.

Abstract: Systems, methods and user interfaces employ clearance or margin determinations in motion planning and motion control for robots in operational environments, the clearance or margin determinations representing an amount of clearance or margin between at least one portion of a robot and one or more objects in the operational environment. Clearances may be displayed in a presentation of motion, for instance displayed in a presentation of a roadmap or a number of paths in a representation of a three-dimensional environment in which the robot operates. Roadmaps may be adjusted based at least in part of determined clearances, for instance based on user input or autonomously.

Abstract: Manifold for a medical/surgical waste collection assembly. A shell includes a proximal end base, and a lip extending proximally from the proximal end base. The lip extends around an outlet opening defined in the proximal end base that is off-centered to a longitudinal axis of the shell. A cap including a cap head is coupled to a side wall of the shell. A drip stop may be seated within a space defined by the lip to cover the outlet opening. An arcuate section of the lip may be flush with an adjacent section of the side wall. The cap head may define a through hole, and a flapper valve unit may be coupled to the cap head with another component having ears extending through the through hole. A fence may extend from the cap head and configured to be grasped by a user.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change. Various aspects of such robot motion planning are implemented in particular systems and methods that facilitate motion planning of the robot for various environments and tasks.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change. Various aspects of such robot motion planning are implemented in particular systems and methods that facilitate motion planning of the robot for various environments and tasks.

Abstract: Methods of assembling a manifold for a medical waste collection system. A flapper valve unit is secured to a head of a cap. A filter element is positioned within a shell. Basket hands of the filter element are fitted between first pairs of ribs of the cap skirt. Fingers of the shell are fitted between second pairs of ribs of the cap skirt. The cap is secured to the shell to cover an open distal end of the shell. A drip stop is secured to the proximal end base of the shell to seat within the outlet opening. Ears may be fitted through holes defined by the flapper valve unit and cap holes defined by the cap so as to snap lock to the head of the cap. The hub of the flapper valve unit may be compressed with the ears snap locked to the head of the cap.

Abstract: The structures and algorithms described herein employ staging poses to facilitate the operation robots operating in a shared workspace or workcell, preventing or at least reducing the risk of collision while efficiently moving robots to one or more goals to perform respective tasks. Motion planning can be performed during runtime, and includes identifying one or more staging poses for a robot to advantageously position or configure a robot whose path is blocked or is expected to be blocked by one or more other robots, monitoring the other robots and moving the robot toward a goal in response to the path becoming unblocked or cleared. The staging pose can be identified using various heuristics to efficiently position or configure the robot to complete its task one its path becomes unblocked or cleared.

Abstract: Methods of assembling a manifold for a medical waste collection system. A flapper valve unit is secured to a head of a cap. A filter element is positioned within a shell. Basket hands of the filter element are fitted between first pairs of ribs of the cap skirt. Fingers of the shell are fitted between second pairs of ribs of the cap skirt. The cap is secured to the shell to cover an open distal end of the shell. A drip stop is secured to the proximal end base of the shell to seat within the outlet opening. Ears may be fitted through holes defined by the flapper valve unit and cap holes defined by the cap so as to snap lock to the head of the cap. The hub of the flapper valve unit may be compressed with the ears snap locked to the head of the cap.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change. Various aspects of such robot motion planning are implemented in particular systems and methods that facilitate motion planning of the robot for various environments and tasks.

Abstract: Methods of assembling a manifold for a medical waste collection system. A flapper valve unit is secured to a head of a cap. A filter element is positioned within a shell. Basket hands of the filter element are fitted between first pairs of ribs of the cap skirt. Fingers of the shell are fitted between second pairs of ribs of the cap skirt. The cap is secured to the shell to cover an open distal end of the shell. A drip stop is secured to the proximal end base of the shell to seat within the outlet opening. Ears may be fitted through holes defined by the flapper valve unit and cap holes defined by the cap so as to snap lock to the head of the cap. The hub of the flapper valve unit may be compressed with the ears snap locked to the head of the cap.

Abstract: Solutions for multi-robot configurations are co-optimized, to at least some degree, across a set of non-homogenous parameters based on a given set of tasks to be performed by robots in a multi-robot operational environment. Non-homogenous parameters may include two or more of: the respective base position and orientation of the robots, an allocation of tasks to respective robots, respective target sequences and/or trajectories for the robots. Such may be executed pre-runtime. Output may include for each robot: workcell layout, an ordered list or vector of targets, optionally dwell time durations at respective targets, and paths or trajectories between each pair of consecutive targets. Output may provide a complete, executable, solution to the problem, which in the absence of variability in timing, can be used to control the robots without any modification. A genetic algorithm, e.g., Differential Evolution, may optionally be used in generating a population of candidate solutions.

Abstract: A system for motion planning for autonomous vehicles can include a plurality of sensors, a plurality of detectors in electrical communication with the plurality of sensors, and a motion planning module in electrical communication with the plurality of detectors and a computing system of an autonomous vehicle. The motion planning module stores a planning graph with each node representing, explicitly or implicitly, time and variables defining a state of the autonomous vehicle, an operating environment, or both the state of the autonomous vehicle and the operating environment. A reconfigurable processor can include a collision detection module and, optionally, a shortest path module. Pre-computed collision data and planning graph data reflecting logical/physical node mapping can be communicated to the processor during a programming phase and used during runtime.

Abstract: A processor-based system provides a user interface to facilitate generation of motion planning graphs or roadmaps, for example via autonomous generate of additional poses, for example neighboring poses, based on specified seed or origin pose, and/or generate or sub-lattice connecting poses and/or edges to couple separate regions or sub-lattices of the motion planning graph together. Such may include performing collision-checking and/or kinematic checking (e.g., taking into account kinematic constraints of robots being modeled). The resulting motion planning graphs or roadmaps are useful in controlling robots during runtime. Robots may include robots with appendages and/or robots in the form of autonomous vehicles.

Abstract: A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

Abstract: A system for motion planning for autonomous vehicles can include a plurality of sensors, a plurality of detectors in electrical communication with the plurality of sensors, and a motion planning module in electrical communication with the plurality of detectors and a computing system of an autonomous vehicle. The motion planning module stores a planning graph with each node representing, explicitly or implicitly, time and variables defining a state of the autonomous vehicle, an operating environment, or both the state of the autonomous vehicle and the operating environment. A reconfigurable processor can include a collision detection module and, optionally, a shortest path module. Pre-computed collision data and planning graph data reflecting logical/physical node mapping can be communicated to the processor during a programming phase and used during runtime.

Abstract: A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change.