UAV/UGV Autonomous Cooperation: UAV Assists UGV to Climb a Cliff by Attaching a Tether

This paper proposes a novel cooperative system for an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) which utilizes the UAV not only as a flying sensor but also as a tether attachment device. Two robots are connected with a tether, allowing the UAV to anchor the tether to a structure located at the top of a steep terrain, impossible to reach for UGVs. Thus, enhancing the poor traversability of the UGV by not only providing a wider range of scanning and mapping from the air, but also by allowing the UGV to climb steep terrains with the winding of the tether. In addition, we present an autonomous framework for the collaborative navigation and tether attachment in an unknown environment. The UAV employs visual inertial navigation with 3D voxel mapping and obstacle avoidance planning. The UGV makes use of the voxel map and generates an elevation map to execute path planning based on a traversability analysis. Furthermore, we compared the pros and cons of possible methods for the tether anchoring from multiple points of view. To increase the probability of successful anchoring, we evaluated the anchoring strategy with an experiment. Finally, the feasibility and capability of our proposed system were demonstrated by an autonomous mission experiment in the field with an obstacle and a cliff.Comment: 7 pages, 8 figures, accepted to 2019 International Conference on Robotics & Automation. Video: https://youtu.be/UzTT8Ckjz1

Study of Mobile Robot Operations Related to Lunar Exploration

Mobile robots extend the reach of exploration in environments unsuitable, or unreachable, by humans. Far-reaching environments, such as the south lunar pole, exhibit lighting conditions that are challenging for optical imagery required for mobile robot navigation. Terrain conditions also impact the operation of mobile robots; distinguishing terrain types prior to physical contact can improve hazard avoidance. This thesis presents the conclusions of a trade-off that uses the results from two studies related to operating mobile robots at the lunar south pole. The lunar south pole presents engineering design challenges for both tele-operation and lidar-based autonomous navigation in the context of a near-term, low-cost, short-duration lunar prospecting mission. The conclusion is that direct-drive tele-operation may result in improved science data return. The first study is on demonstrating lidar reflectance intensity, and near-infrared spectroscopy, can improve terrain classification over optical imagery alone. Two classification techniques, Naive Bayes and multi-class SVM, were compared for classification errors. Eight terrain types, including aggregate, loose sand and compacted sand, are classified using wavelet-transformed optical images, and statistical values of lidar reflectance intensity. The addition of lidar reflectance intensity was shown to reduce classification errors for both classifiers. Four types of aggregate material are classified using statistical values of spectral reflectance. The addition of spectral reflectance was shown to reduce classification errors for both classifiers. The second study is on human performance in tele-operating a mobile robot over time-delay and in lighting conditions analogous to the south lunar pole. Round-trip time delay between operator and mobile robot leads to an increase in time to turn the mobile robot around obstacles or corners as operators tend to implement a `wait and see\u27 approach. A study on completion time for a cornering task through varying corridor widths shows that time-delayed performance fits a previously established cornering law, and that varying lighting conditions did not adversely affect human performance. The results of the cornering law are interpreted to quantify the additional time required to negotiate a corner under differing conditions, and this increase in time can be interpreted to be predictive when operating a mobile robot through a driving circuit

3D Path planning using a fuzzy logic navigational map for Planetary Surface Rovers

This work proposes an innovative app navigation path-planning problem exploration rovers by including terrain characteristics. The objective is to enhance the typical 2D arithmetical cost function by adding 3D information computed from the laser-scanned terrain such as terrain height, slopes, shadows, orientation and terrain roughness. This paper describes the algorithm developed by UPM and GMV and the tests made at the GMV outdoor test facilities using the Moon-Hound rover. This rover is a 50 Kg rover including a Sick laser mounted on a pan&tilt unit for generation of 3D Digital Elevation Models (DEM’s). Experimental results have shown the effectiveness of the proposed approach

Mars Science Laboratory Mission and Science Investigation

Scheduled to land in August of 2012, the Mars Science Laboratory (MSL) Mission was initiated to explore the habitability of Mars. This includes both modern environments as well as ancient environments recorded by the stratigraphic rock record preserved at the Gale crater landing site. The Curiosity rover has a designed lifetime of at least one Mars year (∼23 months), and drive capability of at least 20 km. Curiosity’s science payload was specifically assembled to assess habitability and includes a gas chromatograph-mass spectrometer and gas analyzer that will search for organic carbon in rocks, regolith fines, and the atmosphere (SAM instrument); an x-ray diffractometer that will determine mineralogical diversity (CheMin instrument); focusable cameras that can image landscapes and rock/regolith textures in natural color (MAHLI, MARDI, and Mastcam instruments); an alpha-particle x-ray spectrometer for in situ determination of rock and soil chemistry (APXS instrument); a laser-induced breakdown spectrometer to remotely sense the chemical composition of rocks and minerals (ChemCam instrument); an active neutron spectrometer designed to search for water in rocks/regolith (DAN instrument); a weather station to measure modern-day environmental variables (REMS instrument); and a sensor designed for continuous monitoring of background solar and cosmic radiation (RAD instrument). The various payload elements will work together to detect and study potential sampling targets with remote and in situ measurements; to acquire samples of rock, soil, and atmosphere and analyze them in onboard analytical instruments; and to observe the environment around the rover. The 155-km diameter Gale crater was chosen as Curiosity’s field site based on several attributes: an interior mountain of ancient flat-lying strata extending almost 5 km above the elevation of the landing site; the lower few hundred meters of the mountain show a progression with relative age from clay-bearing to sulfate-bearing strata, separated by an unconformity from overlying likely anhydrous strata; the landing ellipse is characterized by a mixture of alluvial fan and high thermal inertia/high albedo stratified deposits; and a number of stratigraphically/geomorphically distinct fluvial features. Samples of the crater wall and rim rock, and more recent to currently active surface materials also may be studied. Gale has a well-defined regional context and strong evidence for a progression through multiple potentially habitable environments. These environments are represented by a stratigraphic record of extraordinary extent, and insure preservation of a rich record of the environmental history of early Mars. The interior mountain of Gale Crater has been informally designated at Mount Sharp, in honor of the pioneering planetary scientist Robert Sharp. The major subsystems of the MSL Project consist of a single rover (with science payload), a Multi-Mission Radioisotope Thermoelectric Generator, an Earth-Mars cruise stage, an entry, descent, and landing system, a launch vehicle, and the mission operations and ground data systems. The primary communication path for downlink is relay through the Mars Reconnaissance Orbiter. The primary path for uplink to the rover is Direct-from-Earth. The secondary paths for downlink are Direct-to-Earth and relay through the Mars Odyssey orbiter. Curiosity is a scaled version of the 6-wheel drive, 4-wheel steering, rocker bogie system from the Mars Exploration Rovers (MER) Spirit and Opportunity and the Mars Pathfinder Sojourner. Like Spirit and Opportunity, Curiosity offers three primary modes of navigation: blind-drive, visual odometry, and visual odometry with hazard avoidance. Creation of terrain maps based on HiRISE (High Resolution Imaging Science Experiment) and other remote sensing data were used to conduct simulated driving with Curiosity in these various modes, and allowed selection of the Gale crater landing site which requires climbing the base of a mountain to achieve its primary science goals. The Sample Acquisition, Processing, and Handling (SA/SPaH) subsystem is responsible for the acquisition of rock and soil samples from the Martian surface and the processing of these samples into fine particles that are then distributed to the analytical science instruments. The SA/SPaH subsystem is also responsible for the placement of the two contact instruments (APXS, MAHLI) on rock and soil targets. SA/SPaH consists of a robotic arm and turret-mounted devices on the end of the arm, which include a drill, brush, soil scoop, sample processing device, and the mechanical and electrical interfaces to the two contact science instruments. SA/SPaH also includes drill bit boxes, the organic check material, and an observation tray, which are all mounted on the front of the rover, and inlet cover mechanisms that are placed over the SAM and CheMin solid sample inlet tubes on the rover top deck

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion