Robotics and Autonomous Systems

The dataset and the parser of it have been uploaded for reference.

These movies show the experiments in sea and tank environments.

These are each figure's data. The file name shows information of data.

Nonlinear terms of matrices in the nonlinear model singularly perturbed for an omnidirectional wheeled mobile robot. Complementary data associated with the paper entitled "Nonlinear trajectory tracking controller for wheeled mobile robots by using a flexible auxiliary law based on slipping and skidding variations".

The raw data comprising of the values of the number of nodes expanded and the computation times for all the flow directions and the goal locations has been provided in Supplementary Data 1.xlsx Trajectories corresponding to obstacle densities ranging from 30 to 80 and uniformly placed in the environments comprising of ambient flows in all the directions has been provided in Supplementary Data 2.rar The raw data comprising of the values of the number of nodes expanded and the computation times for all the flow directions and the obstacle densities has been provided in Supplementary Data 3.xlsx Flow simulation data corresponding to Section: 9.1.1 Goals Placed at Different Distances has been provided in Supplementary Data 4.rar that comprises of “.csv” files. The name of .csv files are “x _y.csv” were “x” is the number of obstacles and “y” is the flow direction. The data in the .csv file are as follows: Column 1: x-coordinate Column 2: y-coordinate Column 3: x component of flow Column 4: y component of flow Column 5: flow direction in radians Column 6: flow direction in degrees Column 7: flow magnitude Flow simulation data corresponding to Section: 9.1.2 Different Obstacle Densities has been provided in Supplementary Data 5.rar that comprises of .csv files. The name of .csv files are “flow _y.csv” were “y” is the flow direction. The data in the .csv file are as follows: Column 1: x-coordinate Column 2: y-coordinate Column 3: x component of flow Column 4: y component of flow Column 5: flow direction in radians Column 6: flow direction in degrees Column 7: flow magnitude

In Example of Drop Jumping, we show a slow-motion video to demonstrate the jumping behavior of the robot. In Data of Fig. 6, we demonstrate the recorded data for Fig. 6

These are the specifications of each environment used of the manuscript "Motion Planning under Uncertainty in Graduated Fidelity Lattices". **** ENVIRONMENTS **** For each environment the following specifications are given. Units are meters and radians: * Map dimensions: x * Location of the starting pose: (, , ). = 0 is the direction of the positive X. * Goal position: (, ) * min/max position of the location denied areas: (, ) ** FIG 8 - Dimensions: 40.0 x 24.8 m - Starting pose: (5.0, 8.0, 0.0) - Goal position: (34.0, 19.0) - Location denied areas: (6.0, 0.0) to (11.0, 7.0) (9.5, 7.0) to (11.0, 8.5) (12.0, 11.0) to (28.0, 17.5) (13.0, 9.0) to (15.0, 11.0) (32.0, 15.0) to (35.0, 20.0) ** FIG 9 - Dimensions: 65.0 x 40.3 m - Starting pose: (4.0, 16.0, 0.0) - Goal position: (56.0, 8.0) - Location denied areas (9a): None - Location denied areas (9b): (25.0, 0.0) to (52.0, 15.5) - Location denied areas (9c): (25.0, 0.0) to (52.0, 15.5) (25.0, 26.0) to (47.0, 40.0) ** FIG 10 - Dimensions: 35.0 x 25.3 m - Starting pose: (19.0, 20.0, 3.1416) - Goal position: (31.0, 5.0) - Location denied areas: (10.0, 0.0) to (35.0, 25.3) ** FIG 11 - Dimensions: 30.0 x 30.0 m - Starting pose: (7.0, 15.0, -1.5708) - Goal position: (5.0, 23.0) - Location denied areas: None **** PPM FILE FORMAT **** Images are provided in the PPM file format (ASCII). These files have the following structure: # line comment ... ... This is: after the comment lines (starting with "#"), the first two numbers are the image size (in pixels) Then, three values for each RGB pixel are given. Pixels follow a row-major order. Pixels with R < 10; G < 10; B < 10 are considered occupied. Elsewhere is free space. Please, note that contained in these files do not correspond to the dimensions of the environments in the manuscript. Each pixel has a coordinate (X, Y) which is calculated from the resolution of the image and the environment dimensions (DIM_X, DIM_Y): X = PIXEL_X * (DIM_X / N_PIXELS_X) Y = PIXEL_Y * (DIM_Y / N_PIXELS_Y) **** OT FILE FORMAT **** Files to use with the Octomap[1] library are also given. These were generated with Octomap v.1.7.2. These files already have the dimensions used in the experiments and require no additional processing. [1] A. Hornung,. K.M. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, "OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees" in Autonomous Robots, 2013; DOI: 10.1007/s10514-012-9321-0. Software available at http://octomap.github.com.

experiment video of the transformable wheel-legged robot LDR

all programs are compiled by the matlab software, inwhich 3R_simulation and 3R_realexperiment1 are a simulated program and a real-experiment program, sub_3R_G andsub_3R_G2 are two subprograms of 3R_simulation , at last, other programs are subprograms of 3R_realexperiment1.

the two files, 3R_realexperiment.m and 3R_simulation.m, acomplish the simulation and real experiment on the inverse solution of 3R robot, other files are sub-procedures of the two main.