Methods, systems, and apparatus, including computer-readable storage devices, for robot navigation using 2D and 3D path planning. In the disclosed method, a robot accesses map data indicating two-dimensional layout of objects in a space and evaluates candidate paths for the robot to traverse. In response to determining that the candidate paths do not include a collision-free path across the space for a two-dimensional profile of the robot, the robot evaluates a three-dimensional shape of the robot with respect to a three-dimensional shape of an object in the space. Based on the evaluation of the three-dimensional shapes, the robot determines a collision-free path to traverse through the space.

In an embodiment, a method includes determining a given material to manipulate to achieve a goal state. The goal state can be one or more deformable or granular materials in a particular arrangement. The method further includes, for the given material, determining, a respective outcome for each of a plurality of candidate actions to manipulate the given material. The determining can be performed with a physics-based model, in one embodiment. The method further can include determining a given action of the candidate actions, where the outcome of the given action reaching the goal state is within at least one tolerance. The method further includes, based on a selected action of the given actions, generating a first motion plan for the selected action.

Specialized robot motion planning hardware and methods of making and using same are provided. A robot-specific hardware can be designed using a tool that receives a robot description comprising a collision geometry of a robot, degrees of freedom for each joint of the robot, and joint limits of the robot; receives a scenario description; generates a probabilistic roadmap (PRM) using the robot description and the scenario description; and for each edge of PRM, produces a collision detection unit comprising a circuit indicating all parts of obstacles that collide with that edge. The hardware is implemented as parallel collision detection units that provide collision detection results used to remove edges from the PRM that is searched to find a path to a goal position.

A method of controlling a robot within a volume, the method comprising: receiving a three dimensional model including a model of the robot and a model of the volume in which the robot is configured to move within; defining a plurality of positions within the model of the volume to which the robot is moveable to, the plurality of positions being identified by an operator; receiving scanned three dimensional data of the robot and at least a part of the volume; determining a transformation algorithm using the three dimensional model and the scanned three dimensional data; applying the transformation algorithm to one or more positions of the plurality of positions to provide one or more transformed positions; and controlling movement of the robot using one or more of the transformed positions.

A robot control system includes a state candidate generation unit that generates a state candidate that is a state transition destination of a robot at next time, a control amount estimation unit that estimates a control amount for transitioning to the state candidate, a state candidate evaluation unit that calculates a distance between the target state of the robot and the state candidate, calculates a coincidence degree between (i) a state at next time estimated from a state at current time of the robot and the control amount and (ii) the state candidate, and sets a sum of the distance and the coincidence degree to be an evaluation value, and a selection unit that selects a state candidate with a minimum evaluation value from state candidates and generate a motion corresponding to the selected state candidate.

A robot optimization motion planning technique using a refined initial reference path. When a new path is to be computed using motion optimization, a candidate reference path is selected from storage which was previously computed and which has similar start and goal points and collision avoidance environment constraints to the new path. The candidate reference path is adjusted at all state points along its length to account for the difference between the start and goal points of the new path compared to those of the previously-computed path, to create the initial reference path. The initial reference path, adjusted to fit the start and goal points, is then used as a starting state for the motion optimization computation. By using an initial reference path which is similar to the final converged new path, the optimization computation converges more quickly than if a naïve initial reference path is used.

A method includes accessing RGB and depth image data representing a scene that includes at least a portion of a robotic limb. Using this data, a computing system may segment the image data to isolate and identify at least a portion of the robotic limb within the scene. The computing system can determine a current pose of the robotic limb within the scene based on the image data, joint data, or a 3D virtual model of the robotic limb. The computing system may then determine a desired goal pose, which may be based on the image data or the 3D virtual model. Based on the determined goal pose, the computing device determines the difference between the current pose and the goal pose of the robotic limb, and using this difference, provides a pose adjustment that for the robotic limb.

Compositions and methods for treating or preventing the progression of neurodegenerative diseases are provided herein. Exemplary compositions include bacterial compositions having an effective amount of viable, non-pathogenic microbes, viable, non-pathogenic bacteria, wherein at least one of the bacteria is a predatory bacteria such as Bdellovibrio bacteriovorus. The disclosed bacterial compositions can be used to treat or prevent the progression of neurodegenerative diseases such as ALS, Alzheimer's disease, Huntington's disease, and Parkinson's disease.

Techniques are described that determine motion of a robot's body that will maintain an end effector within a useable workspace when the end effector moves according to a predicted future trajectory. The techniques may include determining or otherwise obtaining the predicted future trajectory of the end effector and utilizing the predicted future trajectory to determine any motion of the body that is necessary to maintain the end effector within the useable workspace. In cases where no such motion of the body is necessary because the predicted future trajectory indicates the end effector will stay within the useable workspace without motion of the body, the body may remain stationary, thereby avoiding the drawbacks caused by unnecessary motion described above. Otherwise, the body of the robot can be moved while the end effector moves to ensure that the end effector stays within the useable workspace.

A method of tracking a user position using a crowd robot, a tag device, and a robot implementing the same are disclosed, and the robot includes a controller, which cumulatively stores position information of a tag device, generates a moving route corresponding to the stored position information of the tag device, and corrects the position information of the tag device based on position estimation information of a crowd robot around the tag device sent from the tag device.