Dr Homayoon Kazerooni: Professor at UC-Berkeley, pioneer of exoskeletons, founder and CEO of U.S. Bionics (DBA suitX), founder Ekso Bionics

Purpose The following paper is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD-turned innovator and entrepreneur regarding his pioneering efforts. The paper aims to discuss these issues. Design/methodology/approach The interviewee is Dr Homayoon Kazerooni, Professor of Mechanical Engineering at the University of California (UC) Berkeley, pioneer and leading entrepreneur of robotic exoskeletons. He is a foremost expert in robotics, control sciences, exoskeletons, bioengineering and mechatronics design. Kazerooni shares in this interview details on his second start-up, US Bionics DBA suitX. Findings Kazerooni received his MS and PhD in Mechanical Engineering from the Massachusetts Institute of Technology (MIT). He has been a Professor at UC Berkeley for over 30 years. He also serves as the Director of the Berkeley Robotics and Human Engineering Laboratory “KAZ LAB.” The lab’s early research focused on enhancing human upper extremity strength, and Kazerooni led his team to successfully develop a new class of intelligent assist devices that are currently marketed worldwide and used by manual laborers in distribution centers and factories worldwide. Dr Kazerooni’s later work focused on the control of human–machine systems specific to human lower extremities. After developing BLEEX, ExoHiker and ExoClimber – three load-carrying exoskeletons – his team at Berkeley created Human Universal Load Carrier. It was the first energetically autonomous, orthotic, lower extremity exoskeleton that allowed its user to carry 100-pound weights in various terrains for an extended period, without becoming physically overwhelmed. The technology was initially licensed to Ekso Bionics and then Lockheed Martin. Kazerooni and his team also developed lower-extremity technology to aid persons who have experienced a stroke, spinal cord injuries or have health conditions that obligate them to use a wheelchair. Originality/value In 2005, Kazerooni founded Ekso Bionics, the very first exoskeleton company in America, which went on to become a publicly owned company in 2014. Ekso, currently marketed by Ekso Bionics, was designed jointly between Ekso Bionics and Berkeley for paraplegics and those with mobility disorders to stand and walk with little physical exertion. In 2011, Austin Whitney, a Berkeley student suffering from lower limb paralysis, walked for commencement in one of Kazerooni’s exoskeletons, “The Austin Exoskeleton Project,” named in honor of Whitney. Kazerooni went on in 2011, to found US Bionics, DBA suitX, a venture capital, industry and government-funded robotics exoskeleton company. suitX’s core technology is focused on the design and manufacturing of affordable industrial and medical exoskeletons to improve the lives of workers and people with gait impairment. suitX has received investment from Wistron (Taiwan), been awarded several US government awards and won two Saint-Gobain NOVA Innovation Awards. suitX has also won the US$1m top prize in the “UAE AI and Robotics for Good” Competition. Its novel health-care exoskeleton Phoenix has recently received FDA approval. Kazerooni has won numerous awards including Discover magazine’s Technological Innovation Award, the McKnight-Land Grant Professorship and has been a recipient of the outstanding ASME Investigator Award. His research was recognized as the most innovative technology of the year in New York Times Magazine. He has served in a variety of leadership roles in the mechanical engineering community and served as editor of two journals: ASME Journal of Dynamics Systems and Control and IEEE Transaction on Mechatronics. Kazerooni has published more than 200 articles to date, delivered over 130 plenary lectures internationally and is the inventors of over 100 patents.

Downlink Power Control: A Performance Booster for Full Duplex Cellular Networks

<div><div>Full duplex (FD) communication uses the same time-frequency resource elements for uplink and downlink transmissions. Compared to half-duplex (HD) systems, this improves the effective spectrum usage, but at the cost of additional self-interference and increased co-channel interference (CCI). Promising improvements in full duplex downlink performance are well established in the literature, but the improvement in uplink is marginal or even severely degraded due to strong down-link signals. This paper focuses on managing CCI in an FD network by spatially controlling downlink and uplink transmit powers. We show that uplink performance can be improved through the introduction of downlink power control, but this slightly reduces downlink performance. We introduce a distance-based user scheduling to address this reduction. Furthermore, we have also shown that optimal overall performance can be achieved by designing appropriate uplink and downlink power control factors. We used the Matern Cluster process to model the network. The analytical results we formulated is verified by extensive Monte Carlo simulations. This work is submitted to IEEE transaction on Wireless Communications. Currently it is under review.</div></div>

Downlink Power Control: A Performance Booster for Full Duplex Cellular Networks

<div><div>Full duplex (FD) communication uses the same time-frequency resource elements for uplink and downlink transmissions. Compared to half-duplex (HD) systems, this improves the effective spectrum usage, but at the cost of additional self-interference and increased co-channel interference (CCI). Promising improvements in full duplex downlink performance are well established in the literature, but the improvement in uplink is marginal or even severely degraded due to strong down-link signals. This paper focuses on managing CCI in an FD network by spatially controlling downlink and uplink transmit powers. We show that uplink performance can be improved through the introduction of downlink power control, but this slightly reduces downlink performance. We introduce a distance-based user scheduling to address this reduction. Furthermore, we have also shown that optimal overall performance can be achieved by designing appropriate uplink and downlink power control factors. We used the Matern Cluster process to model the network. The analytical results we formulated is verified by extensive Monte Carlo simulations. This work is submitted to IEEE transaction on Wireless Communications. Currently it is under review.</div></div>

Deep Meta-Learning Energy-Aware Path Planner for Unmanned Ground Vehicles in Unknown Terrains

This paper presents an adaptive energy-aware prediction and planning framework for vehicles navigating over terrains with varying and unknown properties. A novel feature of the method is the use of a deep meta-learning framework to learn a prior energy model, which can efficiently adapt to the local terrain conditions based on small quantities of exteroceptive and proprioceptive data. A meta-adaptive heuristic function is also proposed for the integration of the energy model into an A* path planner. The performance of the proposed approach is assessed in a 3D-body dynamic simulator over several typologies of deformable terrains, and compared with alternative machine learning solutions. We provide evidence of the advantages of the proposed method to adapt to unforeseen terrain conditions, thereby yielding more informed estimations and energy-efficient paths, when navigating on unknown terrains.<div>Submitted for revision to IEEE Transaction on Cybernetics.</div>

Deep Meta-Learning Energy-Aware Path Planner for Unmanned Ground Vehicles in Unknown Terrains

This paper presents an adaptive energy-aware prediction and planning framework for vehicles navigating over terrains with varying and unknown properties. A novel feature of the method is the use of a deep meta-learning framework to learn a prior energy model, which can efficiently adapt to the local terrain conditions based on small quantities of exteroceptive and proprioceptive data. A meta-adaptive heuristic function is also proposed for the integration of the energy model into an A* path planner. The performance of the proposed approach is assessed in a 3D-body dynamic simulator over several typologies of deformable terrains, and compared with alternative machine learning solutions. We provide evidence of the advantages of the proposed method to adapt to unforeseen terrain conditions, thereby yielding more informed estimations and energy-efficient paths, when navigating on unknown terrains.<div>Submitted for revision to IEEE Transaction on Cybernetics.</div>

Interlayer Debonding Inspection in Airport Pavements by MIMO GPR System

&lt;p&gt;The integrity and flatness of airport pavement facilities are important to maintain safe operations of aircrafts. Even a small defect and resulting debris can cause catastrophic accidents and, therefore, anomalies must be accurately detected for the first time before major damage occurs. To this effect, it is necessary to develop a low-cost, efficient, and accurate inspection technology to detect the anomalies in airport concrete pavements. In recent years, non-destructive testing (NDT) methods have been widely used in airport pavement inspection and maintenance due to the provision of reliable and efficient information. Amongst the NDT techniques, GPR can provide optimal resolutions for different applications in civil engineering due to the ultra-wide frequency band configuration [1][2]. However, for the investigation of airport pavement facilities main challenges are how to extract information from the reflections by small anomalies [3][4].&lt;/p&gt;&lt;p&gt;In this research, we used a MIMO GPR system to inspect the interlayer debonding in a large area of an airport pavement. A special set of antenna arrangements of the system can obtain common mid-point (CMP) gathers during a common offset survey simultaneously. The existence of interlayer debonding affects the phase of the reflection signals, and the phase disturbance can be quantified by wavelet transform. Therefore, an advanced approach that uses the average entropy of the wavelet transform parameters in a CMP gathers to detect the interlayer debonding in airport pavements is proposed.&lt;/p&gt;&lt;p&gt;The aim of this research is to provide more significant and accurate information for airport pavement inspections using a MIMO GPR system. To this extent, the wavelet entropy analysis is applied to identify the interlayer debonding existed in the shallow region. The proposed approach was then evaluated by field tests on an airport taxiway. The results were validated by on-site coring and demonstrate that the regions with high entropy correspond to the regions where tiny voids occurred. The proposed method has proven potential to detect the interlayer debonding of the pavement model accurately and efficiently.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References&lt;/p&gt;&lt;p&gt;[1] Alani, A. M. et al., 2020. Reverse-Time Migration for Evaluating the Internal Structure of Tree-Trunks Using Ground-Penetrating Radar. NDT&amp;E International, vol.115, pp:102294.&lt;/p&gt;&lt;p&gt;[2] Zou, L. et al., 2020. Mapping and Assessment of Tree Roots using Ground Penetrating Radar with Low-Cost GPS. Remote Sensing, vol.12, no.8, pp:1300.&lt;/p&gt;&lt;p&gt;[3] Zou, L. et al., 2020. On the Use of Lateral Wave for the Interlayer Debonding Detecting in an Asphalt Airport Pavement Using a Multistatic GPR System. IEEE Transaction on Geoscience and Remote Sensing, vol. 58, no. 6, pp. 4215-4224.&lt;/p&gt;&lt;p&gt;[4] Zou, L. et al., 2021. Study on Wavelet Entropy for Airport Pavement Debonded Layer Inspection by using a Multi-Static GPR System. Geophysics, in press.&lt;/p&gt;

Optimal reactive power dispatch: a bibliometric analysis

Optimal reactive power dispatch (ORPD) plays a significant role in the control and smooth operation of the power system through the enhancement of the network’s reliability, security, and economic aspects. This paper presents a bibliometric and visual analysis of ORPD-related research articles extracted from the Web of Science (WoS) database from its inception to October 29, 2019. A total of 263 articles drawn from 166 journals, published between 1989 and 2019, were retrieved and analysed using Excel, HistCite, and VOSviewer visualisation software. The total number of citations for the 263 articles ranges from 0 to 297. The top three journals with the most significant number of ORPD publications were the International Journal of Electrical Power and Energy Systems, Applied Soft Computing, and two journals qualified for the third place, IEEE Transaction on Power Systems and IET Generation Transmission and Distribution. The most active researcher is Provas Kumar Roy, with nine (9) articles from Kalyani Government Engineering College. The most trending/cited researcher is Yi Jia Cao, with 129 Total Local Citation Scores from Hunan University, Changsha. In terms of contribution by countries, India, China, Iran, and the United States were the most significant contributors with 27.8%, 20.9%, 11.8%, and 8% of the total articles, respectively. The top 5 most frequently used substantive keywords to identify the trending topic and research direction were Particle Swarm Optimisation, Genetic Algorithm, Gravitational Search Algorithm, Linear Programming, Evolutional Algorithm, and Hybrid Algorithm. This study provides a detailed outline and reveals the future research directions for both experienced and novice ORPD researchers to identify research topics, questions, and collaboration partners.

Microstrip Antenna-inception, Progress and Current-state of The Art Review

Background: Microstrip antenna has gained significant attention for a large number of communication systems due to its adaptable features and compatibility. Objective: The major objective of this manuscript is to assess the microstrip antenna technology for structure adaptability, the feature based performance capabilities, design and versatility. Methods: The major reviews conducted in every decade on antenna technology highlighted the significance of microstrip antenna technology. Moreover, a review of the articles on microstrip antenna published in ‘IEEE Transaction on Antenna and Propagation’ revealed that these antennas can primarily be used instead of other types of antennas. : The available presentation of microstrip antennas includes features, such as small size, flatness (low profiles), wide-ranging impedance bandwidth, high gain, and circular polarization. A chronological assessment of the major endeavors in the microstrip antenna study conducted during the last four decades, is highlighted. Results: This manuscript focuses on the cutting-edge developments in the microstrip antenna technology and facilitates various modern designated extents, which provide the readers an insight into the tractability presented by microstrip antennas and their prospective benefits as compared to different types of other antennas like lens antenna, dish antenna, horn antenna, etc. The recent advancements in manufacturing techniques of microstrip antenna are reviewed. A large number of publications on the applications of microstrip antennas, such as communication, sensing, energy harvesting, biomedical relevance etc. are also included to show their importance at present. Conclusion: This article presents a state of the art evaluation of the research carried out on microstrip antennas from the time of their inception to till date. It consolidates the information for the researchers working in this field and will be helpful in enhancing the efforts for the research.