Static and Dynamic Path Planning Using Incremental Heuristic Search

Path planning is an important component in any highly automated vehicle system. In this report, the general problem of path planning is considered first in partially known static environments where only static obstacles are present but the layout of the environment is changing as the agent acquires new information. Attention is then given to the problem of path planning in dynamic environments where there are moving obstacles in addition to the static ones. Specifically, a 2D car-like agent traversing in a 2D environment was considered. It was found that the traditional configuration-time space approach is unsuitable for producing trajectories consistent with the dynamic constraints of a car. A novel scheme is then suggested where the state space is 4D consisting of position, speed and time but the search is done in the 3D space composed by position and speed. Simulation tests shows that the new scheme is capable of efficiently producing trajectories respecting the dynamic constraint of a car-like agent with a bound on their optimality.Comment: Internship Repor

Static and Dynamic Path Planning Using Incremental Heuristic Search

Path planning is an important component in any highly automated vehicle system. In this report, the general problem of path planning is considered first in partially known static environments where only static obstacles are present but the layout of the environment is changing as the agent acquires new information. Attention is then given to the problem of path planning in dynamic environments where there are moving obstacles in addition to the static ones. Specifically, a 2D car-like agent traversing in a 2D environment was considered. It was found that the traditional configuration-time space approach is unsuitable for producing trajectories consistent with the dynamic constraints of a car. A novel scheme is then suggested where the state space is 4D consisting of position, speed and time but the search is done in the 3D space composed by position and speed. Simulation tests shows that the new scheme is capable of efficiently producing trajectories respecting the dynamic constraint of a car-like agent with a bound on their optimality

A Sinusoidal Encoder-to-Digital Converter Based on an Improved Tangent Method

Sinusoidal encoders are used for the measurement of angular position and linear displacement. These provide electrical signals dependent on the sine and cosine of the position θ of their moving part relative to the stationary one. Conventional tangent/cotangent converters for determining θ from the encoder signals produce alternating highly non-linear segments of tangent and cotangent. Lookup tables are used for determining θ. This paper presents a novel converter for estimating θ without the lookup table. The method is based on dividing the circle angular interval into N sections. A crude or coarse measure θ C of the unknown angle θ is first determined by identifying the section in which θ is located. This is followed by the determination of a fine measure θ F . These measures are combined to yield a precise measure of θ; the maximum error of the method depends on N. The converter has been implemented on a dSPACE set and has been successfully tested both with a sensor emulator and a real Hall-Effect sinusoidal encoder. This paper describes full details of the theory, simulation, and experimental results. The experimental results demonstrate excellent agreement with theory and simulation.This work was supported by the Qatar National Research Fund (a member of Qatar Foundation) through UREP under Grant 18-156-2-063.Scopu