Martin Azkarate

Planetary exploration is rapidly gaining importance within the space research community. Autonomous locomotion of rovers requires consideration of several mobility aspects to ensure safety, including avoiding hazardous areas that can cause the robot to become immobilized in soft soil or damaged in sharp terrains. Furthermore, when executing autonomous guidance, selecting an appropriate path to follow is crucial to reduce energy consumption and improve the overall distance traveled by the rover. This directly impacts the rover's performance and the possible scientific outcome of the mission. This paper addresses the optimization of the autonomous locomotion of Mars rovers by acting on the guidance and control layers. Firstly, an enhanced velocity‐based traction controller is proposed to simultaneously address slip and kinematic incompatibilities while permitting omnidirectional motion. The controller acts directly at the wheel command level to improve traction and tracking performances, reducing position and heading errors. This is achieved by enriching the controller's input with the rover's linear and angular velocity error. The performance metrics evaluated within the traction controller are then used to dynamically update the cost map of the environment. Finally, a higher‐level path planner is integrated, considering kino‐dynamic constraints, continuously providing new trajectories according to the map updates to select high‐traction paths. The proposed framework has been validated through simulation and real‐world experiments on the MaRTA rover of ESA's Planetary Robotics Laboratory. The results demonstrate that the proposed approach achieves better tracking performance and up to 62% traction improvements thanks to the enhanced controller and dynamic cost map updates.

Proprioceptive sensors on planetary rovers serve for state estimation and for understanding terrain and locomotion performance. While inertial measurement units (IMUs) are widely used to this effect, force-torque sensors are less explored for planetary navigation despite their potential to directly measure interaction forces and provide insights into traction performance. This paper presents an evaluation of the performance and use cases of force-torque sensors based on data collected from a six-wheeled rover during tests over varying terrains, speeds, and slopes. We discuss challenges, such as sensor signal reliability and terrain response accuracy, and identify opportunities regarding the use of these sensors. The data is openly accessible and includes force-torque measurements from each of the six-wheel assemblies as well as IMU data from within the rover chassis. This paper aims to inform the design of future studies and rover upgrades, particularly in sensor integration and control algorithms, to improve navigation capabilities.

The sample fetch rover (SFR) is a novel surface vehicle studied for Mars sample return (MSR). The rover is designed as a multi-mission transportation system with no scientific payloads on board and the only objective of acquiring sample tubes previously deposited on the surface and delivering them to a lander in a strict timeframe. Its mission imposes demanding requirements, such as traverse distance, timeline, mass, volume, and energy, which necessitate the development of new technologies or the augmentation of existing ones. Following the decision not to implement SFR in the MSR campaign, these technologies are becoming attractive for future rover missions to Mars and to the Moon. This paper summarizes the development of these technologies and their applicability to future use cases. The SFR mission profile and design drivers are described herein, along with the system architecture established in response to them. What follows is an overview of the key technologies studied for SFR, focusing on the most critical or innovative ones, such as locomotion, navigation, and sample tube acquisition. The summary includes the other significant aspects of the design: structure, thermal control, mechanisms, control electronics, power, avionics, and communications. For each of these, the main technological advancements and their relevance to forthcoming rover missions are discussed.

Planetary exploration is rapidly gaining importance within the space research community. Autonomous locomotion of rovers requires consideration of several mobility aspects to ensure safety, including avoiding hazardous areas that can cause the robot to become immobilized in soft soil or damaged in sharp terrains. Furthermore, when executing autonomous guidance, selecting an appropriate path to follow is crucial to reduce energy consumption and improve the overall distance traveled by the rover. This directly impacts the rover’s performance and the possible scientific outcome of the mission. This paper addresses the optimization of the autonomous locomotion of Mars rovers by acting on the guidance and control layers. Firstly, an enhanced velocity-based traction controller is proposed, permitting omnidirectional motion while simultaneously addressing slip and kinematic incompatibilities. The controller acts directly at the wheel command level to further improve traction and tracking performances, reducing position and heading errors. The performance metrics evaluated within the traction controller are then used to dynamically update the cost map of the environment. Finally, a higher-level path planner is integrated considering kino-dynamic constraints, continuously providing new paths according to the map updates. The proposed framework has been validated through simulation and real-world experiments on the MaRTA rover of ESA’s Planetary Robotics Laboratory. The results demonstrated that the proposed controller achieves better traction and tracking performance, further improved by the dynamic cost map updates.

Proprioceptive sensors on planetary rovers serve for state estimation and for understanding terrain and locomotion performance. While inertial measurement units (IMUs) are widely used to this effect, force-torque sensors are less explored for planetary navigation despite their potential to directly measure interaction forces and provide insights into traction performance. This paper presents an evaluation of the performance and use cases of force-torque sensors based on data collected from a six-wheeled rover during tests over varying terrains, speeds, and slopes. We discuss challenges, such as sensor signal reliability and terrain response accuracy, and identify opportunities regarding the use of these sensors. The data is openly accessible and includes force-torque measurements from each of the six-wheel assemblies as well as IMU data from within the rover chassis. This paper aims to inform the design of future studies and rover upgrades, particularly in sensor integration and control algorithms, to improve navigation capabilities.

Dataset acquisitions devised specifically for robotic planetary exploration are key for the advancement, evaluation, and validation of novel perception, localization, and navigation methods in representative environments. Originating in the Bardenas semi-desert in July 2023, the data presented in this Data Descriptor is primarily aimed at Martian exploration and contains relevant rover sensor data from approximately 1.7km of traverses, a high-resolution 3D map of the test area, laser-induced breakdown spectroscopy recordings of rock samples along the rover path, as well as local weather data. In addition to optical cameras and inertial sensors, the rover features a thermal camera and six force-torque sensors. This setup enables, for example, the study of future localization, mapping, and navigation techniques in unstructured terrains for improved Guidance, Navigation, and Control (GNC). The main features of this dataset are the combination of scientific and engineering instrument data, as well as the inclusion of the thermal camera and force-torque sensors in particular.

This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers dynamics, nonlinearities and constraints. The proposed motion planner is based on a sequential multi-stage approach that takes advantage of the warm start on each step. Firstly, a globally optimal and smooth 2D/3D trajectory is generated using the Fast Marching Method. This trajectory is fed as a warm start to a sequential linear quadratic regulator that is able to generate an optimal motion plan without constraints for all the platform actuators. Finally, a feasible motion plan is generated considering the constraints defined in the model. In this respect, the sequential linear quadratic regulator is employed again, taking the previously generated unconstrained motion plan as a warm start. The motion planner has been deployed into the Exomars Testing Rover of the European Space Agency. This rover is an Ackermann-capable planetary exploration testbed that is equipped with a robotic arm. Several experiments were carried out demonstrating that the proposed approach speeds up the computation time and increases the success ratio for a martian sample retrieval mission, which can be considered as a representative use case of goal-constrained trajectory generation for an over-actuated mobile platform.

Planetary exploration has been affected by the ability of rovers to avoid getting trapped on sandy terrains. Currently, the European Space Agency in collaboration with the Russian Federal Space Agency are preparing the ExoMars mission, with the objective of placing a rover on the Martian surface to seek for signs of life. This rover is capable of a novel locomotion mode, commonly called wheel walking. It consists on moving the wheel forward and backward in order to improve traction and escape from terrains with a high slip ratio. The main drawback of this locomotion mode is related to the efficiency in power consumption. Therefore, it should be used only in extreme conditions. The objective of this paper is twofold. First, the definition of an experimental setup, based on a rover prototype, an experimental flat terrain and a mechanism to induce a given slip to the rover. Second, the use of this experimental scenario to validate a method, previously proposed by authors, to estimate the rover slip during the wheel walking locomotion mode.