Augmented Vector Field Navigation Cost Mapping using Inertial Sensors In outdoor field robotics, considering the environmental characteristics is key to improving the efficiency of autonomous navigation. In this context, identifying rough terrain can significantly increase the reliability of operations. This paper addresses the problem of mapping the navigation cost associated with uneven outdoor terrains. We propose an augmented vector field representation obtained only with the use of inertial sensors. The map is determined considering characteristics such as roughness and slope. Experiments were carried out with different robots in realworld environments presenting different terrain characteristics to analyze the quality and efficiency of the mapping process. Results show that the obtained navigation cost maps provide a reliable indication of the ground characteristics of outdoor environments and can be used in the path planning stage.

Improved Planetary Rover Inertial Navigation and Wheel Odometry Performance through Periodic Use of ZeroType Constraints We present an approach to enhance wheeled planetary rover deadreckoning localization performance by leveraging the use of zerotype constraint equations in the navigation filter. Without external aiding, inertial navigation solutions inherently exhibit cubic error growth. Furthermore, for planetary rovers that are traversing diverse types of terrain, wheel odometry is often unreliable for use in localization, due to wheel slippage. For current Mars rovers, computer visionbased approaches are generally used whenever there is a high possibility of positioning error; however, these strategies require additional computational power, energy resources, adequate features in the environment, and significantly slow down the rover traverse speed. To this end, we propose a navigation approach that compensates for the high likelihood of odometry errors by providing a reliable navigation solution that leverages nonholonomic vehicle constraints as well as stateaware pseudomeasurements (e.g., zero velocity and zero angular rate) updates during periodic stops. By using this, computationally expensive visualbased corrections could be performed less often. Experimental tests that compare against GPSbased localization are used to demonstrate the accuracy of the proposed approach. The source code, postprocessing scripts, and example datasets associated with the paper are published in a public repository.