Autonomy in planetary exploration is nowadays in the spotlight since space agencies are preparing different mission to place rovers in other planets and satellites. Although autonomy has been widely researched for terrestrial applications, it remains to be fully adapted to rovers. To solve this issue, the space robotics team from the University of Malaga arises as a spin-off within the Robotics and Mechatronics research group, which has demonstrated wide experience in field robotics and manipulation. Recent activities, in collaboration with ESA, have supported the development of a path and motion planning methods for planetary exploration.
The objective is develop and test in a representative analogue a rover system suitable to increase data collection, perform autonomous long traverse surface exploration, guarantee fast reaction, mission reliability,and optimal exploitation of resources.
Path & Motion Planning for a Sample Fetching Rover (ESA contract No: 4000118072/16/NL/LvH/gp - 2)
Following the Autonomous Routing on Extreme Surfaces (ARES) activity where a dynamic path planning algorithm has been designed capable of routing a reconfigurable rover through an optimal path considering different rover locomotion modes, we plan to continue now on this research topic by adding new features to the onboard control architecture that will allow increase the autonomy of the planetary rover. In a second stage, the previously developed path planning algorithm will be extended to allow a rover to carry a manipulator with the aim of performing some tasks such as sample fetching on remote planets and/or assembly of parts in a future station on the Moon.
Path planning in extreme terrains (ESA contract No: 4000118072/16/NL/LvH/gp).
Dynamic path planning in extreme terrains with reconfigurable rovers arises as an interesting research topic. Although there are some contributions related to path planning for planetary exploration, none of them takes into consideration that a rover can walk using different kinematic configurations. The aim of this project is to modify previously proposed path planning algorithms to take into account different locomotion modes during the traverse.
J Ricardo Sánchez-Ibánez, Carlos J Pérez-del-Pulgar, Martin Azkarate, Levin Gerdes, Alfonso García-Cerezo
|Autonomy on rovers is desirable in order to extend the traversed distance, and therefore, maximize the number of places visited during the mission. It depends heavily on the information that is available for the traversed surface on other planet. This information may come from the vehicle’s sensors as well as from orbital images. Besides, future exploration missions may consider the use of reconfigurable rovers, which are able to execute multiple locomotion modes to better adapt to different terrains. With these considerations, a path planning algorithm based on the Fast Marching Method is proposed. Environment information coming from different sources is used on a grid formed by two layers. First, the Global Layer with a low resolution, but high extension is used to compute the overall path connecting the rover and the desired goal, using a cost function that takes advantage of the rover locomotion modes. Second, the Local Layer with higher resolution but limited distance is used where the path is dynamically repaired because of obstacle presence. Finally, we show simulation and field test results based on several reconfigurable and non-reconfigurable rover prototypes and a experimental terrain.|
Carlos Jesús Pérez del Pulgar Mancebo, Pablo Romeo Manrique, Gonzalo Jesús Paz Delgado, José Ricardo Sánchez Ibáñez, Martin Azkarate
The use of autonomous rovers for planetary exploration is crucial to traverse long distances and perform new discoveries on other planets. One of the most important issues is related to the interaction between the rover wheel and terrain, which would help to save energy and even avoid getting entrapped. The use of reconfigurable rovers with different locomotion modes has demonstrated improvement of traction and energy consumption. Therefore, the objective of this paper is to determine the best locomotion mode during the rover traverse, based on simple parameters, which would be obtained from propioceptive sensors. For this purpose, interaction of different terrains have been modelled and analysed with the ExoTeR, a scale prototype rover of the European ExoMars 2020 mission. This rover is able to perform, among others, the wheel walking locomotion mode, which has been demonstrated to improve traction in different situations. Currently, it is difficult to decide the instant time the rover has to switch from this locomotion mode to another. This paper also proposes a novel method to estimate the slip ratio, useful for deciding the best locomotion mode. Finally, results are obtained from an immersive simulation environment. It shows how each locomotion mode is suitable for different terrains and slopes and the proposed method is able to estimate the slip ratio.
Multi-scale Path planning for a Planetary Exploration Vehicle with Multiple Locomotion Modes
Planetary exploration vehicles (rovers) can encounter with a great variety of situations. Most of them are related to the terrain, which can cause the end of the mission if these vehicles are not able to traverse it. It was the case of Spirit rover, which got stuck in loose sand, making it impossible to continue advancing. A solution to this is to make rovers capable of modifying their locomotion to traverse terrains with particular terramechanic parameters.
C.J. Pérez del Pulgar, J.R. Sánchez, A.J. Sánchez, M. Azkarate and G. Visentin
J.R. Sánchez, C.J. Pérez del Pulgar and M. Azkarate
This paper introduces a path planning algorithm that takes into consideration different locomotion modes in a wheeled reconfigurable rover. Such algorithm, based on Fast Marching, calculates the optimal path in terms of power consumption between two positions, providing the most appropriate locomotion mode to be used at each position. Finally, the path planning algorithm is validated on a virtual Martian scene created within the V-REP simulation platform, where a virtual model of a planetary rover prototype is controlled by the same software that is used on the real one. Results of this contribution also demonstrate how the use of two locomotion modes, wheel-walking and normal-driving, can reduce the power consumption for a particular area.