The leapfrog algorithm, so-called because of its geometric nature, for solving a class of optimal control problems is proposed. Initially a feasible trajectory is given and subdivided into smaller pieces. In each subdivision, with the assumption that local optimal controls can easily be calculated, a piecewise-optimal trajectory is obtained. Then the junctions of these smaller pieces of optimal...

Trajectory tracking is an essential capability of robotics operation in industrial automation. In this article, an artificial neural controller is proposed to tackle trajectory-tracking problem of an autonomous ground vehicle (AGV). The controller is implemented based on fractional order proportional integral derivative (FOPID) control that was already designed in an earlier work. A non-holonom...

We derive a near-time-optimal trajectory for wheeled mobile robots (WMRs) satisfying the following: 1) initial and final postures/velocities as well as 2) battery voltage and armature current constraints, under assumptions of simplified dynamics and constant translational/rotational velocity sections. We use a simplified dynamic model for WMRs neglecting inductances of motor armatures and divid...

Trajectory data capture the traveling history of moving objects such as people or vehicles. With the proliferation of GPS and tracking technology, huge volumes of trajectories are rapidly generated and collected. Under this, applications such as route recommendation and traveling behavior mining call for efficient trajectory retrieval. In this paper, we first focus on distance-based trajectory ...

This work reports on the application of artificial intelligence and neural networks techniques to the problem of trajectory planning and control of a mobile robot with low sensory power. The aim is to determine a spatial sequence through which the robot must navigate forming a trajectory between the starting and goal points. In the first test, the environment has no obstacles and a search tree ...

Visual tracking is the task of estimating the trajectory of an object in a video given its initial location. This is usually done by combining at each step an appearance and a motion model. In this work, we learn from a small set of training trajectory annotations how the objects in the scene typically move. We learn the relative weight between the appearance and the motion model. We call this ...

We consider the problem of video stabilization: removing unwanted image perturbations due to unstable camera motions. We approach this problem from an image-based rendering (IBR) standpoint. Given an unstabilized video sequence, the task is to synthesize a new sequence as seen from a stabilized camera trajectory. This task is relatively straightforward if one has a Euclidean reconstruction of t...

We present HySIA: a reliable runtime verification tool for nonlinear hybrid automata (HA) and signal temporal logic (STL) properties. HySIA simulates an HA with interval analysis techniques so that a trajectory is enclosed sharply within a set of intervals. Then, HySIA computes whether the simulated trajectory satisfies a given STL property; the computation is performed again with interval anal...

A complete stability analysis is performed on a planar system of the form _ = ( ) where is a Hurwitz matrix and is the saturation function. Necessary and sufficient conditions for the system to be globally asymptotically stable (GAS) or to have a closed trajectory are explicitly given in terms of the entries of . These conditions also indicate that the system always has a closed trajectory if i...

This paper provides a closed-form analytical solution to the motion planning problem for the Snakeboard. Given a desired planar trajectory in the fiber space, an explicit solution is computed for the gaits in the base space that locomote the Snakeboard along the desired trajectory. This is achieved by introducing a new momentum-like variable that simplifies the Snakeboard’s equations of motion ...