Browse Topic: Terrain
Usually hosted in Southern California, the Advanced Clean Transportation (ACT) Expo moved about 265 miles (425 km) north and east for its latest edition, taking place in Las Vegas from May 20-23. Interestingly, that distance challenges the range limits of most Class 8 battery-electric trucks, particularly if traversing hilly terrain or hauling heavy loads. One electric truck capable of covering such a stretch - with its estimated range of up to 500 miles (805 km) fully loaded at 82,000 lb GCW - is the Tesla Semi, which made its trade-show debut at the ACT Expo. “Achieving strong range-to-mass ratios is only possible with a dedicated, purpose-built, ground-up electric platform - exactly what the Semi is. There's no wasted space, the powertrain and the vehicle work hand in hand,” Dan Priestley, senior manager of engineering for the Tesla Semi, said during a keynote in Las Vegas.
ANYmal has for some time had no problem coping with the stony terrain of Swiss hiking trails. Now researchers at ETH Zurich have taught this quadrupedal robot some new skills: it is proving rather adept at parkour, a sport based on using athletic maneuvers to smoothly negotiate obstacles in an urban environment, which has become very popular. ANYmal is also proficient at dealing with the tricky terrain commonly found on building sites or in disaster areas.
Centipedes are known for their wiggly walk. With tens to hundreds of legs, they can traverse any terrain without stopping.
A team at NASA's Jet Propulsion Laboratory that's creating a snake-like robot for traversing extreme terrain is taking on the challenge with the mentality of a startup: Build quickly, test often, learn, adjust, repeat. Called EELS (short for Exobiology Extant Life Surveyor), the self-propelled, autonomous robot was inspired by a desire to look for signs of life in the ocean hiding below the icy crust of Saturn's moon Enceladus by descending narrow vents in the surface that spew geysers into space.
In recent decades, significant technological advances have made cruise control systems safer, more automated, and available in more driving scenarios. However, comparatively little progress has been made in optimizing vehicle efficiency while in cruise control. In this paper, two distinct strategies are proposed to deliver efficiency benefits in cruise control by leveraging flexibility around the driver’s requested set speed, and road information that is available on-board in many new vehicles. In today’s cruise control systems, substantial energy is wasted by rigidly controlling to a single set speed regardless of the terrain or road conditions. Introducing even a small allowable “error band” around the set speed can allow the propulsion system to operate in a pseudo-steady state manner across most terrain. As long as the vehicle can remain in the allowed speed window, it can maintain a roughly constant load, traveling slower up hills and faster down hills. This strategy reduces the
Synthetic Aperture Radar (SAR) images are a powerful tool for studying the Earth’s surface. They are radar signals generated by an imaging system mounted on a platform such as an aircraft or satellite. As the platform moves, the system emits sequentially high-power electromagnetic waves through its antenna. The waves are then reflected by the Earth’s surface, re-captured by the antenna, and finally processed to create detailed images of the terrain below.
ABSTRACT Geotechnical site characterization is the process of collecting geophysical and geospatial characteristics about the surface and subsurface to create a 3-dimensional (3D) model. Current Robot Operating System (ROS) world models are designed primarily for navigation in unknown environments; however, they do not store the geotechnical characteristics requisite for environmental assessment, archaeology, construction engineering, or disaster response. The automotive industry is researching High Definition (HD) Maps, which contain more information and are currently being used by autonomous vehicles for ground truth localization, but they are static and primarily used for navigation in highly regulated infrastructure. Modern site characterization and HD mapping methods involve survey engineers working on-site followed by lengthy post processing. This research addresses the shortcomings for current world models and site characterization by introducing Site Model Geospatial System
Autonomous vehicle navigation requires signal processing of the vehicle’s sensors to provide meaningful information to the planners such that challenging artifacts like shadows, rare events, obstructive vegetation, etc. are identified properly, avoiding ill-informed navigation. Using a single algorithm such as semantic segmentation of camera images is often not enough to identify those challenging features but can be overcome by processing more than one type of sensor and fusing their results. In this work, semantic segmentation of camera image and LiDAR point cloud signals is performed using Echo State Networks to overcome the challenge of shadows identified as obstructions in off-road terrains. The coordination of algorithms processing multiple sensor signals is shown to avoid unnecessary road obstructions caused by high-contrast shadows for more informed navigational planning.
ABSTRACT Autonomous vehicles rely on path planning to guide them towards their destination. These paths are susceptible to interruption by impassable hazards detected at the local scale via on-board sensors, and malicious disruption. We define robustness as an additional parameter which can be incorporated into multi-objective optimization functions for path planning. The robustness at any point is the output of a function of the isochrone map at that point for a set travel time. The function calculates the sum of the difference in area between the isochrone map and the isochrone map with an impassable semi-circle hazard inserted in each of the four cardinal directions. We calculate and compare two different Pareto paths which use robustness as an input parameter with different weights. Citation: T. Jonsson Damgaard, M. Rittri, P. Franz, A. Halota “Robust Path Planning in the Battlefield,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA
A team of researchers from the Department of Mechanical Science and Bioengineering at Osaka University have invented a new kind of walking robot that takes advantage of dynamic instability to navigate. By changing the flexibility of the couplings, the robot can be made to turn without the need for complex computational control systems. This work may assist the creation of rescue robots that are able to traverse uneven terrain.
Researchers from MIT’s Improbable Artificial Intelligence Lab, part of the Computer Science and Artificial Intelligence Laboratory (CSAIL), have developed a legged robotic system that can dribble a soccer ball under the same conditions as humans. The bot used a mixture of onboard sensing and computing to traverse different natural terrains such as sand, gravel, mud, and snow, and adapt to their varied impact on the ball’s motion. Like every committed athlete, “DribbleBot” could get up and recover the ball after falling.
A research team led by Professor Jemin Hwangbo of the Department of Mechanical Engineering at KAIST has developed a quadrupedal robot control technology that can walk robustly with agility even in deformable terrain such as sandy beach.
Genesys Aerosystems, a Moog company, offers a line of avionics specifically designed for the military/special-mission market. Originally, the system was developed as part of the FAA's Capstone Program - first established in 1999 - to reduce the excessively high number of controlled flight into terrain (CFIT) accidents in the southeast region of Alaska. Implementation of this technology by pilots in the southeast Alaska region immediately reduced the CFIT accident rate from an average of one fatality every nine days to zero among commercial aircraft. Twenty years later, the Capstone equipment continues to provide exceptional safety, and Genesys has become a leading avionics supplier to military and special-mission fleet operators around the world, including the U.S. Navy, U.S. Army, and over 35 foreign militaries and other government operators.
Genesys Aerosystems, a Moog company, offers a line of avionics specifically designed for the military/special-mission market. Originally, the system was developed as part of the FAA’s Capstone Program — first established in 1999 — to reduce the excessively high number of controlled flight into terrain (CFIT) accidents in the southeast region of Alaska.
An interdisciplinary team of University of Minnesota Twin Cities scientists and engineers has developed a first-of-its-kind, plant-inspired extrusion process that enables synthetic material growth. The new approach will allow researchers to build better soft robots that can navigate hard-to-reach places, complicated terrain, and potentially areas within the human body.
The future battlefield will be filled with multiple dissimilar energy networks including unmanned and manned vehicular platforms actively engaged in cooperative control and communications capable of overpowering an adversary and dominating the battlespace. This chaotic multi-domain operational environment will be limited by variable operating conditions (mission profiles, terrain, atmospheric conditions), copious amounts of real-time actionable intelligence derived from weapon and sensor suites, and most importantly, the energy capabilities of each platform.
ABSTRACT To advance development of the off-road autonomous vehicle technology, software simulations are often used as virtual testbeds for vehicle operation. However, this approach requires realistic simulations of natural conditions, which is quite challenging. Specifically, adverse driving conditions, such as snow and ice, are notoriously difficult to simulate realistically. The snow simulations are important for two reasons. One is mechanical properties of snow, which are important for vehicle-snow interactions and estimation of route drivability. The second one is simulation of sensor responses from a snow surface, which plays a major role in terrain classification and depends on snow texture. The presented work describes an overview of several approaches for realistic simulation of snow surface texture. The results indicate that the overall best approach is the one based on the Wiener–Khinchin theorem, while an alternative approach based on the Cholesky decomposition is the second
ABSTRACT This paper presents a new terrain traversability mapping method integrated into the Robotic Technology Kernel (RTK) that produces ground slope traversability cost information from LiDAR height maps. These ground slope maps are robust to a variety of off-road scenarios including areas of sparse or dense vegetation. A few simple and computationally efficient heuristics are applied to the ground slope maps to produce cost data that can be directly consumed by existing path planners in RTK, improving the navigation performance in the presence of steep terrain. Citation: J. Ramsey, R. Brothers, J. Hernandez, “Creation of a Ground Slope Mapping Methodology Within the Robotic Technology Kernel for Improved Navigation Performance,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 16-18, 2022.
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