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Design and fabrication of an agricultural robot for crop seeding

Materials Today: Proceedings 2023年 81卷 283-289页

作者： Hussain Nor Azmi Sami Salama Hussen Hajjaj Kisheen Rao Gsangaya Mohamed Thariq Hameed Sultan Mohd Fazly Mail Lee Seng Hua Department of Mechanical Engineering Universiti Tenaga Nasional Jalan IKRAM-UNITEN Kajang Selangor Darul Ehsan 43000 Malaysia Centre for Advanced Mechatronics and Robotics (CaMaRo) Universiti Tenaga Nasional Jalan IKRAM-UNITEN Kajang Selangor Darul Ehsan 43000 Malaysia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Jalan IKRAM-UNITEN Kajang Selangor Darul Ehsan 43000 Malaysia Laboratory of Biocomposite Technology Institute of Trop‘ical Forestry and Forest Products (INTROP) Universiti Putra Malaysia UPM Serdang Selangor Darul Ehsan 43400 Malaysia Department of Aerospace Engineering Faculty of Engineering Universiti Putra Malaysia UPM Serdang Selangor Darul Ehsan 43400 Malaysia Aerospace Malaysia Innovation Centre (944741-A) Prime Minister’s Department MIGHT Partnership Hub Jalan Impact Cyberjaya Selangor Darul Ehsan 63000 Malaysia Farm Mechanization Program Engineering Research Centre Malaysian Agricultural Research and Development Institute (MARDI) Serdang Selangor Darul Ehsan 43400 Malaysia Laboratory of Biopolymer and Derivatives Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia Serdang Selangor Darul Ehsan 43400 Malaysia

Crop seeding is a time-consuming and tedious activity for farmers and is only exacerbated in large agriculture fields. Manually sowing seeds by hand is a highly inefficient process that requires a lot of human effort and can lead to health concerns for farmers, while spreading seedlings using tractors results in a high wastage of seedlings. This research paper describes the development of a low-cost agricultural robot for crop seeding. The prototype system consists of two parts, namely a mobile base for robot movement and a seeding mechanism attached to the mobile base for crop seeding application. The mobile base has a four-wheel design to ease movement on uneven terrains, while the seeding mechanism uses the concept of a crank-slider to continuously inject seedlings into the ground. Crop seeding tests show that the robot is able to sow 138 seedlings in 5 min, with an accuracy of 92%, compared to 102 seedlings by human workers. This demonstrates an increase in the crop seeding efficiency of over 35%. As for the battery life test, it was determined that the robot can function for up to 4 h on a single charge. Thus, there will not be an increase in the operation time and reduction in the efficiency of the crop seeding process due to the recharging times when human workers are replaced with the prototype system. The recharging duration for the robot power supply is 1.5 h. While the prototype system has successfully achieved its objective of reducing human interference, labour requirement, and the overall operating costs in the field of agriculture for crop seeding process, by making the robot fully autonomous, using either a rail- or line-following system, labour costs can be further reduced as an operator is not required to manually steer the robot to each seeding path.

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Opportunistic synthesis in reactive games under information asymmetry

arXiv

引用

arXiv 2019年

作者： Kulkarni, Abhishek N. Fu, Jie Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01604 United States Department of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01604 United States

Reactive synthesis is a class of methods to construct a provably-correct control system, referred to as a robot, with respect to a temporal logic specification in the presence of a dynamic and uncontrollable environment. This is achieved by modeling the interaction between the robot and its environment as a two-player zero-sum game. However, existing reactive synthesis methods assume both players to have complete information, which is not the case in many strategic interactions. In this paper, we use a variant of hypergames to model the interaction between the robot and its environment;which has incomplete information about the specification of the robot. This model allows us to identify a subset of game states from where the robot can leverage the asymmetrical information to achieve a better outcome, which is not possible if both players have symmetrical and complete information. We then introduce a novel method of opportunistic synthesis by defining a Markov Decision Process (MDP) using the hypergame under temporal logic specifications. When the environment plays some stochastic strategy in its perceived sure-winning and sure-losing regions of the game, we show that by following the opportunistic strategy, the robot is ensured to only improve the outcome of the game—measured by satisfaction of sub-specifications—whenever an opportunity becomes available. We demonstrate the correctness and optimality of this method using a robot motion planning example in the presence of an adversary. Copyright © 2019, The Authors. All rights reserved.

关键词： Specifications

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Revealing preference in popular music through familiarity and brain response

arXiv

引用

arXiv 2021年

作者： Sangnark, Soravitt Autthasan, Phairot Ponglertnapakorn, Puntawat Chalekarn, Phudit Sudhawiyangkul, Thapanun Trakulruangroj, Manatsanan Songsermsawad, Sarita Assabumrungrat, Rawin Amplod, Supalak Ounjai, Kajornvut Wilaiprasitporn, Theerawit Bio-inspired Robotics and Neural Engineering Lab. School of Information Science and Technology Vidyasirimedhi Institute of Science & Technology Rayong Thailand Vision and Learning Lab. School of Information Science and Technology Vidyasirimedhi Institute of Science & Technology Rayong Thailand School of Energy Science and Engineering Vidyasirimedhi Institute of Science & Technology Rayong Thailand Biological Engineering program Faculty of Engineering Neuroscience Center for Research and Innovation Learning Institute King Mongkut’s University of Technology Thonburi Thailand Faculty of Electrical Engineering Sirindhorn International Institute of Technology Thammasat University Thailand School of Engineering Tohoku University Japan

Music preference was reported as a factor, which could elicit innermost music emotion, entailing accurate ground-truth data and music therapy efficiency. This study executes statistical analysis to investigate the distinction of music preference through familiarity scores, response times (response rates), and brain response (EEG). Twenty participants did self-assessment after listening to two types of popular music’s chorus section: music without lyrics (Melody) and music with lyrics (Song). We then conduct a music preference classification using a support vector machine, random forest, and k-nearest neighbors with the familiarity scores, the response rates, and EEG as the feature vectors. The statistical analysis and F1-score of EEG are congruent, which is the brain’s right side outperformed its left side in classification performance. Finally, these behavioral and brain studies support that preference, familiarity, and response rates can contribute to the music emotion experiment’s design to understand music, emotion, and listener. Not only to the music industry, the biomedical and healthcare industry can also exploit this experiment to collect data from patients to improve the efficiency of healing by music. © 2021, CC BY-NC-ND.

关键词： Decision trees

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Approximate Dynamic programming with Probabilistic Temporal Logic Constraints

Approximate Dynamic Programming with Probabilistic Temporal ...

引用

American Control Conference

作者： Lening Li Jie Fu Robotics Engineering Program Worcester Polytechnic Institute Worcester MA 01609 USA

ISBN: (纸本)9781538679012;9781538679265

In this paper, we develop approximate dynamic programming methods for stochastic systems modeled as Markov Decision Processes, given both soft performance criteria and hard constraints in a class of probabilistic temporal logic called Probabilistic Computation Tree Logic (PCTL). Our approach consists of two steps: First, we show how to transform a class of PCTL formulas into chance constraints that can be enforced during planning in stochastic systems. Second, by integrating randomized optimization and dynamic programming with softmax Bellman operator, we devise a novel trajectory sampling-based approximate value iteration method to iteratively solve for an upper bound on the value function while ensuring the constraints that PCTL specifications are satisfied. Particularly, we show that by the on-policy sampling of the trajectories, a tight bound can be achieved between the upper bound given by the approximation and the true value function. The correctness and efficiency of the method are demonstrated using robotic motion planning examples.

关键词： approximation theory dynamic programming iterative methods Markov processes probabilistic logic stochastic systems temporal logic dynamic programming Temporal logic stochastic systems Markov chain Probabilistic logic iterative methods Approximation Theory Upper bound

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Region-based planning for 3D within-hand-manipulation via variable friction robot fingers and extrinsic contacts

arXiv

引用

arXiv 2020年

作者： Sahin, Alp Spiers, Adam J. Calli, Berk Robotics Engineering Program Worcester Polytechnic Institute 85 Prescott Street WorcesterMA01605 United States The Electrical and Electronic Engineering Department Imperial College London LondonSW7 2AZ United Kingdom

Attempts to achieve robotic Within-Hand-Manipulation (WIHM) generally utilize either high-DOF robotic hands with elaborate sensing apparatus or multiarm robotic systems. In prior work we presented a simple robot hand with variable friction robot fingers, which allow a low-complexity approach to within-hand object translation and rotation, though this manipulation was limited to planar actions. In this work we extend the capabilities of this system to 3D manipulation with a novel region-based WIHM planning algorithm and utilizing extrinsic contacts. The ability to modulate finger friction enhances extrinsic dexterity for three-dimensional WIHM, and allows us to operate in the quasi-static level. The region-based planner automatically generates 3D manipulation sequences with a modified A* formulation that navigates the contact regions between the fingers and the object surface to reach desired regions. Central to this method is a set of object-motion primitives (i.e. within-hand sliding, rotation and pivoting), which can easily be achieved via changing contact friction. A wide range of goal regions can be achieved via this approach, which is demonstrated via real robot experiments following a standardized in-hand manipulation benchmarking protocol. © 2020, CC BY-NC-SA.

关键词： Robotic arms

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Opportunistic Synthesis in Reactive Games under Information Asymmetry

Opportunistic Synthesis in Reactive Games under Information ...

引用

Annual Allerton Conference on Communication, Control, and Computing

作者： Jie Fu Department of Electrical and Computer Engineering Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

Reactive synthesis [1]is used to synthesize a provably-correct strategy (controller) with respect to a given Linear Temporal Logic (LTL) specification in a dynamic, potentially adversarial environment. The core idea of reactive synthesis is to model the interaction between a controlled agent (called the robot) and its dynamic and uncontrollable environment as a two-player turn-based zero-sum game. In particular, players' Boolean payoffs are specified by temporal logic formulas [2]-a rich language that can expressive properties such as safety, liveness, stability, and temporally extended goals.

关键词： Games Robots Task analysis Game theory Vehicle dynamics Computer security

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Haptic display for virtual reality: progress and challenges

引用

Virtual Reality & Intelligent Hardware 2019年第2期1卷 136-162页

作者： Dangxiao WANG Yuan GUO Shiyi LIU Yuru ZHANG Weiliang XU Jing XIAO State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Biomedical Engineering Beihang UniversityBeijing 100083China Peng Cheng Laboratory Shenzhen 518055China Department of Mechanical Engineering University of AucklandAuckland 1142New Zealand School of Computer Science and the Robotics Engineering Program Worcester Polytechnic InstituteWorcesterMA 01609-2280USA

Immersion, interaction, and imagination are three features of virtual reality (VR). Existing VR systems possess fairly realistic visual and auditory feedbacks, and however, are poor with haptic feedback, by means of which human can perceive the physical world via abundant haptic properties. Haptic display is an interface aiming to enable bilateral signal communications between human and computer, and thus to greatly enhance the immersion and interaction of VR systems. This paper surveys the paradigm shift of haptic display occurred in the past 30 years, which is classified into three stages, including desktop haptics, surface haptics, and wearable haptics. The driving forces, key technologies and typical applications in each stage are critically reviewed. Toward the future high-fidelity VR interaction, research challenges are highlighted concerning handheld haptic device, multimodal haptic device, and high fidelity haptic rendering. In the end, the importance of understanding human haptic perception for designing effective haptic devices is addressed.

关键词： Haptic display Virtual reality Desktop haptics Surface haptics Wearable haptics Multimodal haptics

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Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities

arXiv

引用

arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh The Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan The Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Radar shows great potential for autonomous driving by accomplishing long-range sensing under diverse weather conditions. But radar is also a particularly challenging sensing modality due to the radar noises. Recent works have made enormous progress in classifying free and occupied spaces in radar images by leveraging lidar label supervision. However, there are still several unsolved issues. Firstly, the sensing distance of the results is limited by the sensing range of lidar. Secondly, the performance of the results is degenerated by lidar due to the physical sensing discrepancies between the two sensors. For example, some objects visible to lidar are invisible to radar, and some objects occluded in lidar scans are visible in radar images because of the radar's penetrating capability. These sensing differences cause false positive and penetrating capability degeneration, respectively. In this paper, we propose training data preprocessing and polar sliding window inference to solve the issues. The data preprocessing aims to reduce the effect caused by radar-invisible measurements in lidar scans. The polar sliding window inference aims to solve the limited sensing range issue by applying a near-range trained network to the long-range region. Instead of using common Cartesian representation, we propose to use polar representation to reduce the shape dissimilarity between long-range and near-range data. We find that extending a near-range trained network to long-range region inference in the polar space has 4.2 times better IoU than in Cartesian space. Besides, the polar sliding window inference can preserve the radar penetrating capability by changing the viewpoint of the inference region, which makes some occluded measurements seem non-occluded for a pretrained network. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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Rats: A robotic arm training system designed for rats

Rats: A robotic arm training system designed for rats

引用

ASME 2020 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2020

作者： Zhang, Haohan Luna, Tatiana Yang, Lillian Martin, John Agrawal, Sunil Robotics and Rehabilitation Laboratory Dept. of Mechanical Engineering Columbia University New YorkNY10027 United States CUNY School of Medicine City College of New York New YorkNY10031 United States Dept. of Molecular Cellular and Biomedical Sciences Center for Discovery and Innovation CUNY School of Medicine Neuroscience Program CUNY Graduate Center New YorkNY10031 United States

ISBN: (纸本)9780791883990

This paper presents a novel robotic system to characterize and retrain reaching in rats. This robot is intended to be a research platform for rehabilitation of forelimb movements in rats. In this paper, we focus on the design of this robotic system. We present the design requirements, mathematical models, and details of the physical device. A parallel mechanism with a special alignment of the component chains is used to accommodate observed reaching motions of a rat’s forelimb. Additionally, we demonstrate the use of this robot to record forelimb trajectories. Three healthy rats were used to record repeated reaching motions while the robot applied nearly zero force. We believe that this robotic system can be used in future training studies with rats who have impaired arm motions due to a neurological insult. Copyright © 2020 ASME

关键词： Rats

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Balancing domain gap for object instance detection

arXiv

引用

arXiv 2019年

作者： Yun, Woo-han Lee, Jaeyeon Kim, Jaehong Kim, Junmo Robotics Program KAIST and Intelligent Robotics Research Division ETRI Korea Republic of Intelligent Robotics Research Division ETRI Korea Republic of School of Electrical Engineering KAIST Korea Republic of

Object instance detection in cluttered indoor environment is a core functionality for service robots. We can readily build a detection system by following recent successful strategy of deep convolutional neural networks, if we have a large annotated dataset. However, it is hard to prepare such a huge dataset in instance detection problem where only small number of samples are available. This is one of main impediment to deploying an object detection system. To overcome this obstacle, many approaches to generate synthetic dataset have been proposed. These approaches confront the domain gap or reality gap problem stems from discrepancy between source domain (synthetic training dataset) and target domain (real test dataset). In this paper, we propose a simple approach to generate a synthetic dataset with minimum human effort. Especially, we identify that domain gaps of foreground and background are unbalanced and propose methods to balance these gaps. In the experiment, we verify that our methods help domain gaps to balance and improve the accuracy of object instance detection in cluttered indoor environment. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

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