Browse Topic: Terrain
Performing transportation and exploration tasks on rugged terrain requires both high load-bearing capacity and large suspension stroke. However, the corner module configurations applied to challenging terrain have rarely been explored. This article proposes an integrated framework that combines bionic principles with topology graph–based type synthesis. This framework leads to the creation of a reconfigurable wheel-legged mechanism capable of switching between wheeled locomotion and legged gait modes, which is then implemented as a corner module system. First, inspired by the skeletal–muscular system of the equine leg, a structure–function mapping relationship between the biological system and the mechanical system is established. Second, a multi-loop closed-chain mechanism with biomimetic morphology is represented in the form of graph theory. A configuration atlas of the wheel-legged hybrid mechanism is generated based on the contracted graph and open-loop kinematic chains, and configuration optimization is carried out. Third, on the basis of the optimized configuration, a biomimetic vibration isolation system is integrated. Finally, a corner module system that integrates the reconfigurable wheel-legged mechanism with steering, hub motor is designed, as well as the mechanical structure of modular transporters based on the aforementioned corner modular architecture. The vibration reduction performance and various locomotion modes of the modular transporter are verified by multibody dynamic simulation.
As countries race to expand renewable energy infrastructure, balancing clean electricity production with land use for food remains a pressing challenge — especially in Japan, where mountainous terrain limits space. A recent study led by researchers from the University of Tokyo explores a promising solution: integrating solar panels with traditional rice farming in a practice known as agrivoltaics.
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical models and dynamic torque monitoring techniques to estimate the weight of bales immediately after the bale wrap process, before the bale is dropped onto the field. With the capability to function effectively in off-road conditions and diverse terrains, this system represents a substantial technological advancement that addresses the evolving challenges of modern agriculture. By demonstrating the potential of this design, the paper illustrates how advanced engineering solutions can enhance resource allocation, optimize feed management and distribution, support long-term planning, and contribute to the sustainability of agricultural practices without incurring additional costs. The weight of each bale can be used by farmers to analyze the current harvest based on bale weight variability and to make improvements before the next harvest. It also aids in key decision-making processes such as bale handling, transportation, sales and storage for future seasons. This advancement has significant advantages for scalability and profitability, allowing for optimized decision-making processes in agricultural operations.
Tippers transporting loose bulk cargo during prolonged descents are subject to two critical operational challenges: cargo displacement and rear axle lifting. Uncontrolled cargo movement, often involving loose aggregates or soil, arises due to gravitational forces and insufficient restraint systems. This phenomenon can lead to cabin damage, loss of control, and hazardous discharge of materials onto roadways. Simultaneously, load imbalances during descent can cause rear axle lift, increasing stress on the front steering axle, resulting in tire slippage and compromised maneuverability. This study proposes a dynamic control strategy that adjusts the tipper lift angle in real time to align with the descent angle of the road. By synchronizing the trailer bed angle with the slope of the terrain, the system minimizes cargo instability, maintains rear axle contact, and enhances braking performance, including engine and exhaust braking systems. Computational modelling is employed to assess the performance of this approach across varying road gradients, vehicle speeds, and terrain characteristics. The paper further outlines the development of an automated control system for real-time angle adjustment and its integration into the vehicle’s existing electrical architecture.
The success of off-road missions for ground vehicles depends heavily on terrain traversability, which in turn requires a thorough understanding of soil characteristics a key component being soil moisture content. When large areas need to be analyzed, satellite imagery is often used, although this approach typically reduces the spatial resolution. This decrease of spatial resolution creates what are known as mixed pixels, when two or more classes or features are in a single pixel’s area, which can lead to noisier data and lower accuracy models. This paper investigates using linear spectral unmixing as a way to help clean / mitigate noisy data to yield better predictive models. Hyperspectral remote sensing from the Hyperion satellite platform and ground truth from the International Soil Moisture Network (ISMN) are used for the dataset. This study found that soil moisture content prediction, comparing the mixed multilayer perceptron (MLP) model with an unmixing approach revealed a 10–30% change in RMSE and MAE across NDVI ranges incremented by 0.1. Hence, this study demonstrates the potential use of spectral unmixing as a methodology to help enhance predictive models for terrain properties when using (lower spatial resolution / more noisy) remotely sensed datasets.
Specialized robots that can both fly and drive typically touch down on land before attempting to transform and drive away. But when the landing terrain is rough, these robots sometimes get stuck and are unable to continue operating. Now a team of Caltech engineers has developed a real-life Transformer that has the “brains” to morph in midair, allowing the dronelike robot to smoothly roll away and begin its ground operations without pause. The increased agility and robustness of such robots could be particularly useful for commercial delivery systems and robotic explorers.
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.
Army rotorcraft operations demand precision and adaptability to navigate challenging terrain, respond to real-time mission requirements, and ensure time-to-target arrival. Navigating complex terrain, making real-time trajectory adjustments, and ensuring timely arrival at designated objectives while considering other problems are challenging. This paper focuses on the concept of 4D conformal pilot cueing that can facilitate a significant reduction in pilot workload. To enhance the rotorcraft operations with Army scenarios, a visual cueing method based on Tau Theory for obstacle avoidance is proposed so that the pilot can make a coordinated turn away from the obstacle and safely change the helicopter's trajectory to avoid the collision. To demonstrate the visual cueing method, desktop simulations are performed in Matlab/Simulink environment using simulated pilots.
Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner. Vehicle apparent temperature-aware kinodynamic motion planning MPC was developed to minimize the vehicle thermal signature metric -- while respecting local mobility constraints due to the terrain grade to prevent vehicle rollover. Additionally, a surface energy model with the inclusion of a vegetation layer was developed to simulate the apparent temperature of the background terrain. The effectiveness of the developed algorithm is demonstrated for the scenario where the adversarial threat perspective is assumed to be from the top looking down at the vehicle.
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 frequency of transient events (e.g. powertrain downshifts, enrichment following fuel cut-off) and the dramatic inefficiencies that result, particularly in ICE applications. The two strategies mentioned differ based on the propulsion control system’s knowledge of the anticipated elevation profile. Where upcoming elevation information is not known, a reactive strategy is used. This maintains efficient optimized steady-state operation for as long as possible, but then takes corrective action when vehicle speed approaches the boundaries of the allowed speed window. Where elevation of upcoming roads is known, a more capable predictive strategy is used. This can anticipate severe grades in advance and make milder corrections over longer time periods to avoid sharp transient behavior. Both strategies demonstrate that significant improvements in fuel economy and EV range can be achieved by relaxing the requirement that cruise control maintain a single constant speed at all times.
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 (SMGS). This site model leverages an octree spatial data model to store heterogeneous geotechnical information in a Volumetric Pixel (Voxel) grid, which allows for more efficient algorithms in data analysis and fusion. SMGS provides a real-time, dynamically updated, 3D data model with semantically derived costmaps for navigation and Engineer operations, ground truth localization without GPS, and produces standard Geographic Information System (GIS) maps. Citation: M. Richards, K. Murphy, I. Lopez Toledo, A. Soylemezoglu, “A Semantically Classified Geo-spatial 3D Octree Voxel Based System for Geotechnical Site Characterization,” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 15-17, 2023.
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, Novi, MI, Aug. 15-17, 2023.
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.
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