Subcritical and supercritical granular flow around an obstacle on a rough inclined plane

A blunt obstacle in the path of a rapid granular avalanche generates a bow shock (a jump in the avalanche thickness and velocity), a region of static grains upstream of the obstacle, and a grain-free region downstream. Here, it is shown that this interaction is qualitatively altered if the incline on which the avalanche is flowing is changed from smooth to rough. On a rough incline, the friction between the grains and the incline depends on the flow thickness and speed, which allows both rapid (supercritical) and slow (subcritical) steady uniform avalanches. For supercritical experimental flows, the material is diverted around a blunt obstacle by the formation of a bow shock and a static dead zone upstream of the obstacle. Downslope, a grain-free vacuum region forms, but, in contrast to flows on smooth beds, static levees form at the boundary between the vacuum region and the flow. In slower, subcritical, flows the flow is diverted smoothly around the dead zone and the obstacle without forming a bow shock. After the avalanche stops, signatures of the dead zone, levees and (in subcritical flows) a deeper region upslope of the obstacle are frozen into the deposit. To capture this behaviour, numerical simulations are performed with a depth-averaged avalanche model that includes frictional hysteresis and depth-averaged viscous terms, which are needed to accurately model the flowing and deposited regions. These results may be directly relevant to geophysical mass flows and snow avalanches, which flow over rough terrain and may impact barriers or other infrastructure.

Development of a Novel Underground Mine Reconnaissance Robot

<p>Despite advancements in safety technology, underground mining disasters kill hundreds of people each year. Typically after a disaster, a manned response team will enter the hazardous mine to ascertain its condition and rescue any survivors. A robotic entry platform could significantly reduce the risk to the response teams and the time taken to recover any survivors. However, existing mine search and rescue robots have had limited success in past disasters. Two primary aspects caused the failure of the existing platforms; poor rough terrain ability and lack of ingress protection for the harsh mine environment. HADES, a novel underground mine reconnaissance robot is developed to address these issues. A lightweight yet robust chassis is manufactured from fibreglass. To allow HADES to operate in the potentially explosive atmosphere, the chassis is protected with a positive pressure gas system, designed to meet the ANZ60079.29 standard. This chassis is sealed against the mine environment with a series of O-rings and lip seals. Whegs are used as the primary locomotion method and are driven with a planetary gearbox and a brushless DC motor. To further improve a rough terrain capability of the locomotion system the rear arm of the chassis is mounted on an actuated pivot, increasing the rough terrain capability of HADES. To ensure the operator can successfully assess and navigate the mine, HADES carries a comprehensive set of environmental and navigation sensors. The internal electronics and locomotion systems are powered with six Li-Po batteries that achieve an operating time of six hours and an expected range of 25 km. HADES is 780x800x400 mm and is mostly sealed to the IP68 standard. The locomotion system is robust and can traverse the majority of the terrain expected in an underground mine. Loss of traction is the only problem encountered with the Wheg design. However, this can be easily fixed by changing the tip shape of the Wheg.</p>

Development of a Novel Underground Mine Reconnaissance Robot

<p>Despite advancements in safety technology, underground mining disasters kill hundreds of people each year. Typically after a disaster, a manned response team will enter the hazardous mine to ascertain its condition and rescue any survivors. A robotic entry platform could significantly reduce the risk to the response teams and the time taken to recover any survivors. However, existing mine search and rescue robots have had limited success in past disasters. Two primary aspects caused the failure of the existing platforms; poor rough terrain ability and lack of ingress protection for the harsh mine environment. HADES, a novel underground mine reconnaissance robot is developed to address these issues. A lightweight yet robust chassis is manufactured from fibreglass. To allow HADES to operate in the potentially explosive atmosphere, the chassis is protected with a positive pressure gas system, designed to meet the ANZ60079.29 standard. This chassis is sealed against the mine environment with a series of O-rings and lip seals. Whegs are used as the primary locomotion method and are driven with a planetary gearbox and a brushless DC motor. To further improve a rough terrain capability of the locomotion system the rear arm of the chassis is mounted on an actuated pivot, increasing the rough terrain capability of HADES. To ensure the operator can successfully assess and navigate the mine, HADES carries a comprehensive set of environmental and navigation sensors. The internal electronics and locomotion systems are powered with six Li-Po batteries that achieve an operating time of six hours and an expected range of 25 km. HADES is 780x800x400 mm and is mostly sealed to the IP68 standard. The locomotion system is robust and can traverse the majority of the terrain expected in an underground mine. Loss of traction is the only problem encountered with the Wheg design. However, this can be easily fixed by changing the tip shape of the Wheg.</p>

Assessing the Utility of Sentinel-1 Coherence Time Series for Temperate and Tropical Forest Mapping

This study tested the ability of Sentinel-1 C-band to separate forest from other common land use classes (i.e., urban, low vegetation and water) at two different sites. The first site is characterized by temperate forests and rough terrain while the second by tropical forest and near-flat terrain. We trained a support vector machine classifier using increasing feature sets starting from annual backscatter statistics (average, standard deviation) and adding long-term coherence (i.e., coherence estimate for two acquisitions with a large time difference), as well as short-term (six to twelve days) coherence statistics from annual time series. Classification accuracies using all feature sets was high (>92% overall accuracy). For temperate forests the overall accuracy improved by up to 5% when coherence features were added: long-term coherence reduced misclassification of forest as urban, whereas short-term coherence statistics reduced the misclassification of low vegetation as forest. Classification accuracy for tropical forests showed little differences across feature sets, as the annual backscatter statistics sufficed to separate forest from low vegetation, the other dominant land cover. Our results show the importance of coherence for forest classification over rough terrain, where forest omission error was reduced up to 11%.

Condition analysis of a multicopter carried with passive skid for rough terrain landing

This paper describes the condition analysis of a multicopter carried with a proposed device for rough terrain landing. Based on a multicopter carried with an electrical robot arm for grasping, we proposed a method to determine whether the skid-carried multicopter can land on an arbitrary slope or not. We established the static model of the entire device, and analyzed the conditions under which the arm and skid can contact the arbitrary plane and the COG (Center of Gravity), which includes the mass of passive skid, multicopter body and each link of the robot arm. Further, we proposed a method to analyze whether the entire device can land stably. By analyzing that the projection of the entire device’s COG is inside or outside the triangle, that comprises the contact point between the device and the uneven ground, we can determine whether the device can land successfully and the condition for capable landing is concluded. After the numerical analysis, the verification experiment is conducted, and by comparing the result of analysis with the experiment, the accuracy of the analysis can be demonstrated.

Extending assistive devices: using the existing interface versus using a new interface

The current research examined whether or not the interface of an extender attached to an assistive device should be identical to the interface of the assistive device. Given the profile of assistive devices such as wheelchairs and the need to extend them in special cases such when maneuvering over rough terrain or obstacles such as stairs and steep inclines, the interface design of these extenders (attached to existing assistive devices) should be evaluated. We have simulated a carrying platform for a wheelchair that is larger than the user’s regular wheelchair. We have examined whether participants used to handling their wheelchair, when asked to operate the carrying platform, handle the latter’s interface better or worse than their wheelchair’s interface. Participants (61) were assigned to one of two between-participants groups. Both groups were trained to navigate a wheelchair using the wheelchair’s interface and then operated the carrying platform. The Familiar Interface group navigated the carrying platform using the wheelchair’s interface, and the New Interface group navigated it with a new interface. The results demonstrated that the Familiar Interface group took longer to perform the task and collided more often with obstacles, compared to the New Interface group. The greater number of collisions can be linked directly to an erroneous mental model of the carrying platform’s size. The insights we reach can be linked to both extenders attached to an assistive device and other technological extenders.

Design and Analysis of Building Diagnostics Robot

This research paper is based on the designing and analysis of a track-based robot which has the capability of climbing stairs and rough terrain maneuverability with an IR sensor to conduct infrared thermography of buildings. The data generated by this can be used to detect and optimize HVAC systems, moisture damage and Electrical issues. The robot is designed in Solidworks software and motion analysis is done using Adams and structural analysis through Ansys. The Thermal imaging camera was tested in the real world to check the feasibility and accuracy of Infrared Thermography.