Abstract: Systems and methods for an imaging system having a memory with a historical localization dictionary database having geo-located driving image sequences, such that each reference image is applied to a threshold to produce a binary representation. A sensor to acquire a sequence of input images of a dynamic scene. An encoder to determine, for each input image in the sequence, a histogram of each input image indicating a number of vertical edges at each bin of the input image and to threshold the histogram to produce a binary representation of the input image. A visual odometer to compare the binary representations of each input image and each reference image, by matching an input image against a reference image. Wherein the visual odometer determines a location of the input image based on a match between the input image and the reference image.

Abstract: A tire of a vehicle is calibrated based on a motion model of the vehicle relating control inputs to the vehicle with a state of the vehicle and a measurement model of the vehicle relating measurements of the motion of the vehicle with the state of the vehicle. The motion model of the vehicle includes a combination of a deterministic component of the motion and a probabilistic component of the motion, wherein the deterministic component of the motion is independent from the state of stiffness and defines the motion of the vehicle as a function of time. The probabilistic component of the motion includes the state of stiffness having an uncertainty and defining disturbance on the motion of the vehicle.

Abstract: A control system of a vehicle for controlling motion of the vehicle traveling on a road shared with a set of moving objects include a memory to store a set of regions of states of lateral dynamic of the vehicle corresponding to a set of equilibrium points. Each region defines a control invariant set of the states of the lateral dynamic determined such that the vehicle having a state within a region is capable to maintain its states within the region, wherein each region includes a corresponding equilibrium point and intersects with at least one adjacent region.

Abstract: A method controls a motion of the host vehicle in the environment according to a trajectory and adjusts the trajectory of the vehicle based on the levels of risk posed by the motion of other vehicles. The method determines a set of feasible trajectories of hypothetical vehicles traveling in a driving area of the host vehicle and determines a level of risk of each feasible trajectory as a combination of the probability of the feasible trajectory to intersect with the trajectory of the host vehicle and the probability of the feasible trajectory to be followed by at least one vehicle. The method adjusts the trajectory of the host vehicle in response to assessing the levels of risk of the feasible trajectories.

Abstract: A tire of a vehicle is calibrated based on a motion model of the vehicle relating control inputs to the vehicle with a state of the vehicle and a measurement model of the vehicle relating measurements of the motion of the vehicle with the state of the vehicle. The motion model of the vehicle includes a combination of a deterministic component of the motion and a probabilistic component of the motion, wherein the deterministic component of the motion is independent from the state of stiffness and defines the motion of the vehicle as a function of time. The probabilistic component of the motion includes the state of stiffness having an uncertainty and defining disturbance on the motion of the vehicle.

Abstract: A method jointly estimates a state of a vehicle including a velocity and a heading rate of the vehicle and a state of stiffness of tires of the vehicle including at least one parameter defining an interaction of at least one tire of the vehicle with a road on which the vehicle is traveling. The method uses the motion and measurement models that include a combination of deterministic component independent from the state of stiffness and probabilistic components dependent on the state of stiffness. The method represents the state of stiffness with a set of particles. Each particle includes a mean and a variance of the state of stiffness defining a feasible space of the parameters of the state of stiffness.

Abstract: Systems and methods for controlling a motion of an object from an initial location to a final location within a region while avoiding a set of obstacles located in the region. The systems and methods include selecting, the equilibrium points within the obstacle-free region of the region, and each equilibrium point includes a corresponding controller driving the object to the equilibrium point, such that each controller includes a corresponding state partition. Designing the controller and the corresponding state partition, based on the obstacle-free region around the equilibrium point, to produce a collection of controllers and corresponding equilibrium points and corresponding state partitions, that connect the initial location with the final location. Determining actuator commands at time T using a controller corresponding to a state partition that includes the location of the object at time T, and the resulting sequence over a period of time of actuator commands, moves the object.

Abstract: A method determines iteratively a motion of the vehicle from an initial location and a target location. An iteration of the method determines a location between the initial location and the target location that satisfies spatial constraints on locations of the vehicle and determines state transitions of the vehicle moved to the location from a set of neighboring locations determined during previous iterations. The method selects a neighboring location resulting in an optimal state transition of the vehicle and updates a graph of state transitions of the vehicle determined during previous iterations with the optimal state transition. The motion of the vehicle is determined a sequence of state transitions connecting the initial location with the target location and the vehicle is controlled according to the determined motion.

Abstract: A method jointly estimates a state of a vehicle including a velocity and a heading rate of the vehicle and a state of stiffness of tires of the vehicle including at least one parameter defining an interaction of at least one tire of the vehicle with a road on which the vehicle is traveling. The method uses the motion and measurement models that include a combination of deterministic component independent from the state of stiffness and probabilistic components dependent on the state of stiffness. The method represents the state of stiffness with a set of particles. Each particle includes a mean and a variance of the state of stiffness defining a feasible space of the parameters of the state of stiffness.

Abstract: A method and a system generate a time-series signal indicative of a variation of the environment in vicinity of the vehicle with respect to a motion of the vehicle and submit the time-series signal to the neural network to produce a reference trajectory as a function of time that satisfies time and spatial constraints on a position of the vehicle. The neural network is trained in to transform time-series signals to reference trajectories of the vehicle. The motion trajectory tracking the reference trajectory while satisfying constraints on the motion of the vehicle is determined and the motion of the vehicle is controlled to follow the motion trajectory.

Abstract: Systems and methods for controlling a motion of an object from an initial location to a final location within a region while avoiding a set of obstacles located in the region. The systems and methods include selecting, the equilibrium points within the obstacle-free region of the region, and each equilibrium point includes a corresponding controller driving the object to the equilibrium point, such that each controller includes a corresponding state partition. Designing the controller and the corresponding state partition, based on the obstacle-free region around the equilibrium point, to produce a collection of controllers and corresponding equilibrium points and corresponding state partitions, that connect the initial location with the final location. Determining actuator commands at time T using a controller corresponding to a state partition that includes the location of the object at time T, and the resulting sequence over a period of time of actuator commands, moves the object.

Abstract: A method and a system generate a time-series signal indicative of a variation of the environment in vicinity of the vehicle with respect to a motion of the vehicle and submit the time-series signal to the neural network to produce a reference trajectory as a function of time that satisfies time and spatial constraints on a position of the vehicle. The neural network is trained in to transform time-series signals to reference trajectories of the vehicle. The motion trajectory tracking the reference trajectory while satisfying constraints on the motion of the vehicle is determined and the motion of the vehicle is controlled to follow the motion trajectory.

Abstract: A method selects from a memory a first model of motion of vehicle, a second model of the motion of the vehicle, a first constraint on the first model for moving along a desired trajectory of the vehicle, and a control invariant set joining states of the first model with states of the second model. For each combination of the states within the control invariant subset there is at least one control action to the second model that maintains the state of the second model within the control invariant set for every modification of the state of the first model satisfying the first constraint. A portion of the desired trajectory satisfying the first constraint is determined using the first model while a sequence of commands for moving the vehicle along the portion of the desired trajectory is determined using the second model.

Abstract: A method jointly estimates a state of a vehicle including a velocity and a heading rate of the vehicle and a state of stiffness of tires of the vehicle including at least one parameter defining an interaction of at least one tire of the vehicle with a road on which the vehicle is traveling. The method uses the motion and measurement models that include a combination of deterministic component independent from the state of stiffness and probabilistic components dependent on the state of stiffness. The method represents the state of stiffness with a set of particles. Each particle includes a mean and a variance of the state of stiffness defining a feasible space of the parameters of the state of stiffness.

Abstract: A method selects from a memory a first model of motion of vehicle, a second model of the motion of the vehicle, a first constraint on the first model for moving along a desired trajectory of the vehicle, and a control invariant set joining states of the first model with states of the second model. For each combination of the states within the control invariant subset there is at least one control action to the second model that maintains the state of the second model within the control invariant set for every modification of the state of the first model satisfying the first constraint. A portion of the desired trajectory satisfying the first constraint is determined using the first model while a sequence of commands for moving the vehicle along the portion of the desired trajectory is determined using the second model.

Abstract: A method determines iteratively a motion of the vehicle from an initial location and a target location. An iteration of the method determines a location between the initial location and the target location that satisfies spatial constraints on locations of the vehicle and determines state transitions of the vehicle moved to the location from a set of neighboring locations determined during previous iterations. The method selects a neighboring location resulting in an optimal state transition of the vehicle and updates a graph of state transitions of the vehicle determined during previous iterations with the optimal state transition. The motion of the vehicle is determined a sequence of state transitions connecting the initial location with the target location and the vehicle is controlled according to the determined motion.

Abstract: A method controls a motion of a vehicle using a model of the motion of the vehicle that includes an uncertainty. The method samples a control space of possible control inputs to the model of the motion of the vehicle to produce a set of sampled control inputs and determines a probability of each sampled control input to move the vehicle into state satisfying constraints on the motion of the vehicle. The method determines, using the probabilities of the sampled control inputs, a control input having the probability to move the vehicle in the state above a threshold. The control input is mapped to a control command to at least one actuator of the vehicle to control the motion of the vehicle.