The orientation and the angular rates of the body of a robotic vehicle are required for guidance and control of the vehicle. In the current robotic systems these quantities are obtained by the use of inertial sensing systems. Inertial sensing systems involve drift errors which can be significant even after the vehicle has traversed only short distances on the terrain. A different approach is suggested here which guarantees accurate, drift-free sensing of the angular position and rates of the vehicle body. A camera system consisting of two cameras in fixed relationship to one another is made to continuously track two stationary objects. The camera system is mounted on the vehicle body through an actuated three degree of freedom joint. The angular positions and rates of these joints can be used to evaluate the angular positions and rates of the vehicle body. An approximate estimate of the position of the vehicle on the terrain can also be obtained from the sensing system. This can serve as primary system for estimating the vehicle position, or as a backup to a more accurate scheme for obtaining the position of the vehicle on the terrain.

DARTS is a rigid/flexible multibody dynamics toolkit for the modeling and simulation of aerospace and robotic vehicles for engineering applications. In this paper we describe an on-line, browser-based environment using Jupyter notebooks to support training needs for the DARTS software. The suite of curated tutorial notebooks is organized into different topic areas, and into multiple themes within each topic area. The notebooks within a theme use a progression of examples for users to expand their understanding of the software. The topic areas include one on the DARTS multibody dynamics software and another one on the theory underlying the multibody dynamics formulation. We also describe a number of Jupyter extensions that were used — and some developed in house — to enhance the notebook interface for use with the dynamics simulation software. One significant extension we implemented allows the embedding of live 3D visualizations within simulation notebooks.

A novel nonlinear planetary rover wheel/soil interaction model based on the properties of the penetration volume is proposed. This approach allows for fast multibody dynamic simulation of planetary rover operations by providing a closed-form solution for the contact forces. For the derivation of this contact model, the normal stress distribution under the planetary rover wheel is assumed to be a nonlinear function of the soil compression. The soil foundation with which the wheels of a robotic vehicle may interfere is represented by a continuum of hyperelastic springs. A linear version of this representation of the contact interface as a mattress of springs has been derived previously [1] and validated for the simulation of the interaction between two relatively inflexible objects [2]. However, for contacts involving large deformations, the nonlinear material properties have to be considered. In this paper, a brief summary of the elastic foundation model is given and the extension of the model to a hyperelastic foundation is provided so that it can be used for the intended purpose of modelling rover wheels in contact with soft terrain. A solution for the integral of the normal stress distribution of the rover wheels is proposed and verified in a number of numerical experiments by comparing the results against Bekker’s analytical approach. Although the focus of this work is on wheel/soil interaction, the general form of the volumetric contact modelling approach can be applied to any hyperelastic contact problem.

We have developed an intensive, three-week summer robotics program for high school students. The program requires special teaching methods since it is offered to rising 10th through 12th grade students with diverse backgrounds, and a low student/teacher ratio to ensure all students grasp the material. We use a project-based learning approach, assigning the students a series of specially tailored labs and projects designed to engage and challenge while preparing them for the main element of the program, the design of a semi-autonomous robotic vehicle whose mission emulates that of NASA’s Martian rovers. The project culminates with testing of their vehicles on an obstacle course. A series of targeted design reviews are held as the project unfolds to keep all designs on schedule. We leverage the spirit of competition to heighten the enthusiasm of the students and sustain their interest through the long-hours required to design and build a successful robot. The students get hands-on experience with mechanism design, electronics, computer-aided-design and manufacturing, and microprocessor programming, and are engaged in discussions on applications of robotics in both academia and industry to provide a “grounding” of the material.

Magnetic sensing is a reliable technology that has been developed for the purposed of position measurement and guidance, especially for applications in autonomous robotic vehicles. To calculate a position of a magnetic guidance road, it should be estimated in real-time. While the capability of a microprocessor and memory spaces have the limitation in implementation. To solve the above problems, this paper proposes a new structure of the magnetic sensors included a vertical magnetic field. The proposed method uses the linear region of the sensor output, and position determination using a simple equation with a microcontroller. The position sensing technique was implemented in the guidance of autonomous vehicle. The test results show that position sensing can be useful for an autonomous robotic vehicle.