An obstacle detection method for unmanned ground vehicle in outdoor environment is proposed. The proposed method uses range data acquired by laser range finders (LRFs) and FMCW radars. LRFs and FMCW radars are used for distinguishing ground and obstacles on uneven terrain, and for detecting obstacles in dusty environment. The proposed obstacle detection algorithm is broadly composed of three steps: 1) 1D virtual range data generation which ground information is removed by range data of LRFs, 2) 1D virtual range data generation acquired by fusion of multiple FMCW radars, 3) 1D virtual range data generation which dust information is removed by fusion of step 1) and step 2). The proposed method is verified by real experiments.
Global path planning (GPP) is the generation of an optimal trajectory to efficiently move from one position to specified
target position with known environment. Most of GPP methodologies offer an optimal 2D-shortest path without
considering vehicle parameters on the plain environments. However, it is motivated to consider 3D terrain and vehicle
parameters to enhance traversability on the rough terrain. In this paper, we propose a novel approach of GPP method for
unmanned ground vehicles (UGVs) by applying distance transform (3D to 2D) based on the slope of terrain. In addition,
the generated path is modified by smoothing process based on the local path planning method which considers vehicle
stability on the specified candidate curve and speed. The proposed methodology is tested by simulations and shows
A new impedance measurement methodology based on time-frequency
domain reflectometry (TFDR) is proposed. For the evaluation of the
reflection coefficient in time-frequency domain reflectometry, the
distortion of the reflected wave by the frequency-dependent
attenuation is compensated which otherwise results in inaccurate
impedance measurement. Also, the phase difference between the
incident and reflected waveforms caused by the state of the load
impedance is evaluated by the cross time-frequency distribution
which provides time-frequency localized phase difference
information. The proposed methodology is verified by a set of
numerical electromagnectic simulation experiments and the results
are compared with classical time domain reflectometry (TDR).
Impedance measurement via time-frequency domain reflectometry is
more accurate over a wider range of impedances than TDR.