Biologically inspired perching for aerial robots

2021 Spring.Includes bibliographical references.Micro Aerial Vehicles (MAVs) are widely used for various civilian and military applications (e.g., surveillance, search, and monitoring, etc.); however, one critical problem they are facing is the limited airborne time (less than one hour) due to the low aerodynamic efficiency, low energy storage capability, and high energy consumption. To address this problem, mimicking biological flyers to perch onto objects (e.g., walls, power lines, or ceilings) will significantly extend MAVs' functioning time for surveillance or monitoring related tasks. Successful perching for aerial robots, however, is quite challenging as it requires a synergistic integration of mechanical and computational intelligence. Mechanical intelligence means mechanical mechanisms to passively damp out the impact between the robot and the perching object and robustly engage the robot to the perching objects. Computational intelligence means computation algorithms to estimate, plan, and control the robot's motion so that the robot can progressively reduce its speed and adjust its orientation to perch on the objects with a desired velocity and orientation. In this research, a framework for biologically inspired perching is investigated, focusing on both computational and mechanical intelligence. Computational intelligence includes vision-based state estimation and trajectory planning. Unlike traditional flight states such as position and velocity, we leverage a biologically inspired state called time-to-contact (TTC) that represents the remaining time to the perching object at the current flight velocity. A faster and more accurate estimation method based on consecutive images is proposed to estimate TTC. Then a trajectory is planned in TTC space to realize the faster perching while satisfying multiple flight and perching constraints, e.g., maximum velocity, maximum acceleration, and desired contact velocity. For mechanical intelligence, we design, develop, and analyze a novel compliant bistable gripper with two stable states. When the gripper is open, it can close passively by the contact force between the robot and the perching object, eliminating additional actuators or sensors. We also analyze the bistability of the gripper to guide and optimize the design of the gripper. At the end, a customized MAV platform of size 250 mm is designed to combine computational and mechanical intelligence. A Raspberry Pi is used as the onboard computer to do vision-based state estimation and control. Besides, a larger gripper is designed to make the MAV perch on a horizontal rod. Perching experiments using the designed trajectories perform well at activating the bistable gripper to perch while avoiding large impact force which may damage the gripper and the MAV. The research will enable robust perching of MAVs so that they can maintain a desired observation or resting position for long-duration inspection, surveillance, search, and rescue

Dynamic Modeling and Simulation of SAG Mill Circuits with Pebble Crushing

Grinding is one of the most energy-consuming processes in the mining industry. As a critical part of the comminution process, autogenous grinding (AG) or semi-autogenous grinding (SAG) mills are often used for primary grinding. However, the breakage mechanism of an AG/SAG mill is inefficient in grinding particles of a certain size, typically in the range of 25-55 mm, i.e., pebbles. Therefore, cone crushers are often used as pebble crushers and integrated into AG/SAG mill circuits to break the critical size particles that accumulate in the mill and to increase the performance of the primary grinding circuits.Many studies have been carried out, mainly focusing on optimizing of SAG mills and cone crushers, respectively, but only a few have investigated the dynamic interactions between a SAG mill and its pebble crushers. The scope of this thesis is to examine the dynamic relations between the SAG mill and the pebble crusher in a closed circuit and thus to optimize the circuit efficiency by controlling the pebble crusher operational settings.In this thesis, two modeling techniques are proposed for simulating the dynamics in the grinding process. The first method is the fundamental modeling method, where the underlying physics of the comminution process has been considered. The proposed mill model is divided into sub-processes that include breakage behavior in each sub-division, particle transportation within the mill chamber, and the discharge rate from the mill. The dynamic cone crusher model describes the crusher chamber as a surge bin and predicts the product particle sizes based on crusher CSS and eccentric speed. In the simulation model, other production units such as screens and conveyors are included to describe the dynamics of the circuit better. The flexibility of this method allows one to apply this simulation library to a variety of plants with different configurations.The second modeling technique presented in this study is based on data-driven methods, where two SAG mill power models are developed. The first model calculates the mill power draw by combining several individual data-driven algorithms. The second model uses historical data to forecast the mill power draw in advance. These data-driven methods can make high accuracy predictions based on a specific plant dataset, and find complex nonlinear relations between input variables and target outputs.The results from both simulations and industrial data analysis show that significant dynamic impact can be induced by altering the pebble crusher operational settings. Therefore, the performance (throughput or specific energy) of an AG/SAG closed circuit can be improved with the optimized utilization of its recycle pebble crusher. While the present work is based on simulation and analysis of plant data, full-scale tests and further model development are needed as part of a future study

OLD city space from the perspective of multi community — Take a floating population community in H city as an example

Taking the specific practice of an old city space as an example, this paper distinguishes the positions and practices of three actors in the space: Urban planners, managers and ordinary citizens hold an extreme modernist position, firmly believing that the old urban space needs to be removed and transformed into a new urban order; Citizens living in the old city space hold a more complex and contradictory position. As the bottom group of the city, they pay attention to the exchange value of community space, but it is difficult to change their living conditions, while maintaining the exclusion of the old city space and the floating population; The floating population builds the old urban space into a space for production and life, making it a "settled community" entering the city. Finally, the diverse position and practice of the old city space show its significance of urbanization and its important role in the construction of urban diversity

Number Translation and Unit Conversion Using Machine Learning

Machine translation is widely utilized to translate text between different language pairs. Applications of automatic translation include content localization. Different regions of the world utilize different measurement units (e.g., acre vs. hectare). Correctly converting and translating measurement units is thus an important part of content localization. Current machine translation models have low accuracy when translating numbers and are unable to handle unit conversions. This disclosure describes techniques to train a machine learning model such that it can generate accurate translations of numbers, including unit conversions. A base model is trained using input text that is tokenized, including splitting numbers into individual digits. Parameters of the trained base model are used to initialize a custom model that is fine-tuned using training data that has been augmented to include annotations, e.g., different values and units for each measurement in the source text. The trained custom model described can deliver correct number translations and unit conversions and can be used for content localization

Public perspective towards social impact of chang e lunar probe program

The present article is based on the MA thesis of Hou Bowen (Ph.D candidate) and on the presentation made at the ISA World Congress of Sociology held in Yokohama (Japan) on July 2014 at the Session on “Assessing Technologies: Global Patterns of Trust and Distrust” of RC23-Sociology of Science and Technology.During the past decades, assessing the impact of technological project and related engineering has long been paid attention. The objective of this research is to investigate technological project and related engineering’s social impact through public perspective. The present article investigated the social impact of China’s Chang E Lunar Probe project by using Social Impact Assessment (SIA) methods, resulting from a research study conducted in 2012. SIA is a collective of the systematic methods used to investigate the influence of engineering, project or policy and to present their potential social impacts. A survey from public respondents indicated that public spoke highly of Chang E Probe on the whole. Furthermore, a factor analysis of the perspective of public perspective towards Chang E Lunar Probe project has discovered such impact were mainly assessed in four dimensions by public, these impacts were military impact, political impact, public support and educational impact. From the results obtained so far, it revealed that public perspective towards the political impact of the Chang E Probe varies from each other but unified when they assess Chang E’s military impact, meanwhile student’s perspective towards the educational impact of Chang E Probe was largely different from other publics.The MA thesis has the supervision of Prof. Yin Haijie (professor in Harbin Institute of Technology)

Image Process of Rock Size Distribution Using DexiNed-Based Neural Network

In an aggregate crushing plant, the crusher performances will be affected by the variation from the incoming feed size distribution. Collecting accurate measurements of the size distribution on the conveyors can help both operators and control systems to make the right decisions in order to reduce overall power consumption and avoid undesirable operating conditions. In this work, a particle size distribution estimation method based on a DexiNed edge detection network, followed by the application of contour optimization, is proposed. The proposed framework was carried out in the four main steps. The first step, after image preprocessing, was to utilize a modified DexiNed convolutional neural network to predict the edge map of the rock image. Next, morphological transformation and watershed transformation from the OpenCV library were applied. Then, in the last step, the mass distribution was estimated from the pixel contour area. The accuracy and efficiency of the DexiNed method were demonstrated by comparing it with the ground-truth segmentation. The PSD estimation was validated with the laboratory screened rock sample

Experimental demonstrations of high-Q superconducting coplanar waveguide resonators

We designed and successfully fabricated an absorption-type of superconducting coplanar waveguide (CPW) resonators. The resonators are made from a Niobium film (about 160 nm thick) on a high-resistance Si substrate, and each resonator is fabricated as a meandered quarter-wavelength transmission line (one end shorts to the ground and another end is capacitively coupled to a through feedline). With a vector network analyzer we measured the transmissions of the applied microwave through the resonators at ultra-low temperature (e.g., at 20 mK), and found that their loaded quality factors are significantly high, i.e., up to 10^6. With the temperature increases slowly from the base temperature (i.e., 20 mK), we observed the resonance frequencies of the resonators are blue shifted and the quality factors are lowered slightly. In principle, this type of CPW-device can integrate a series of resonators with a common feedline, making it a promising candidate of either the data bus for coupling the distant solid-state qubits or the sensitive detector of single photons.Comment: Accepted by Chinese Science Bulleti