This paper presents a motion control method for mobile robots in partially unknown environments populated with moving obstacles. The proposed method is based on the integration of focused D* search algorithm and dynamic window local obstacle avoidance algorithm with some adaptations that provide efficient avoidance of moving obstacles. The moving obstacles are modelled as moving cells in the occupancy grid map and their motion is predicted by applying a procedure similar to the dynamic window approach. The collision points of the robot predicted trajectory and moving cells predicted trajectories form the new active obstacles in the environment, which should be avoided. The algorithms are implemented and verified using a Pioneer 3DX mobile robot equipped with laser range finder.

We present a method for real-time computation of clothoid coordinates that guarantees bounded approximation error over a wide range of clothoid parameters provided that the clothoid's orientation change and length areReal-time approximation bounded. It is shown that coordinates of clothoid with any parameters can be computed from those of a single clothoid (with fixed parameters), using appropriate geometrical transformations. A comprehensive analysis is given on how to determine a required set of clothoids and, based on this, how to sample a clothoid in a lookup table in order to achieve required approximation precision. The algorithm is computationally very efficient and therefore suitable for real-time path planning, as well as for other applications that benefit from fast clothoid computation.

An electronic throttle is a dc-motor-driven valve that regulates air inflow into the combustion system of the engine. The throttle control system should ensure fast and accurate reference tracking of the valve plate angle while preventing excessive wear of the throttle components by constraining physical variables to their normal-operation domains. These high-quality control demands are hard to accomplish since the plant is burdened with strong nonlinear effects of friction and limp-home nonlinearity. In this paper, the controller synthesis is performed in discrete time by solving a constrained time-optimal control problem for the piecewise affine (PWA) model of the throttle. To that end, a procedure is proposed to model friction in a discrete-time PWA form that is suitable both for simulation and controller design purposes. The control action computation can, in general, be restated as a mixed-integer program. However, due to the small sampling time, solving such a program online (in a receding horizon fashion) would be very prohibitive. This issue is resolved by applying recent theoretical results that enable offline precomputation of the state-feedback optimal control law in the form of a lookup table. The technique employs invariant set computation and reachability analysis. The experimental results on a real electronic throttle are reported and compared with a tuned PID controller that comprises a feedforward compensation of the process nonlinearities. The designed time-optimal controller achieves considerably faster transient, while preserving other important performance measures, like the absence of overshoot and static accuracy within the measurement resolution

In this paper, the problem of path planning for active simultaneous localization and mapping (SLAM) is addressed. In order to improve its localization accuracy while autonomously exploring an unknown environment the robot needs to revisit positions seen before. To that end, we propose a path planning algorithm for active SLAM that continuously improves robot's localization while moving smoothly, without stopping, toward a goal position. The algorithm is based on the D* shortest path graph search algorithm with negative edge weights for finding the shortest path taking into account localization uncertainty. The proposed path planning algorithm is suitable for exploration of highly dynamic environments with moving obstacles and dynamic changes in localization demands. While the algorithm operation is illustrated in simulation experiments, its effectiveness is verified experimentally in real-world scenarios.