Article
Biotechnology & Applied Microbiology
Santiago Arroyave-Tobon, Jordan Drapin, Anton Kaniewski, Jean-Marc Linares, Pierre Moretto
Summary: This study evaluated the effects of modeling uncertainties on kinematic simulations at small scale, developed a multibody model of a Messor barbarus ant, and acquired kinematic data using high-speed cameras. The results showed that the model was more sensitive to perturbations on marker position, which is of interest for locomotion studies of small quadrupeds and other multi-legged animals.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Giovanni Colucci, Andrea Botta, Luigi Tagliavini, Paride Cavallone, Lorenzo Baglieri, Giuseppe Quaglia
Summary: This paper presents a kinematic model and motion planning pipeline for a mobile manipulator designed for precision agriculture applications, consisting of a novel mobile base and a commercial manipulator. The linear mapping of the differential kinematics of the custom system is expressed as a function of input commands. A motion planning algorithm based on manipulator manipulability and closed form inverse kinematics is proposed for pick-and-place tasks.
Article
Automation & Control Systems
Keunwoo Jang, Jiyeong Baek, Suhan Park, Jaeheung Park
Summary: This article proposes an efficient motion planner based on a probabilistic roadmap that can successfully compute the path for object manipulation using a multiarm under a closed-chain constraint.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Mechanical
Jun Ha Sohn, Seunghwa Oh, Chang-Ho Lee, Sung-Soo Kim
Summary: The study introduces the recursive inverse kinematics (RIK) algorithm for calculating joint angles of a humanoid robot, validated through experiments in an indoor environment. Comparison between virtual humanoid robot movements and human movements were made to evaluate the algorithm's effectiveness.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Zhan Li, Shuai Li
Summary: In this paper, a simplified RNN approach is proposed for redundancy resolution with RCM constraints, demonstrating efficiency and convergence properties. The theoretical analysis and simulation results highlight the effectiveness of the method in end-effector path tracking control under RCM constraints for redundant manipulators.
NEURAL PROCESSING LETTERS
(2022)
Article
Computer Science, Information Systems
Matheus C. Santos, Lucas Molina, Elyson A. N. Carvalho, Eduardo O. Freire, Jose G. N. Carvalho, Phillipe C. Santos
Summary: The paper introduces a new probabilistic inverse kinematics solver based on the Rapidly-Exploring Random Tree (RRT) method, growing the tree as a spatial representation of the manipulator on the workspace to reduce the search space and improve performance by incorporating a new probability model and metric for the closest node.
Article
Chemistry, Multidisciplinary
Matteo Russo, Marco Ceccarelli, Daniele Cafolla
Summary: This paper presents a model-based motion planning approach for cable-driven compliant mechanisms with a flexible backbone. A novel kinematic model is introduced to describe and analyze the torso mechanism for humanoid robots, improving the accuracy and efficiency of the system.
APPLIED SCIENCES-BASEL
(2021)
Article
Agriculture, Multidisciplinary
Lei Ye, Jieli Duan, Zhou Yang, Xiangjun Zou, Mingyou Chen, Sheng Zhang
Summary: The study utilized the APSO algorithm and the AtBi-RRT algorithm for collision-free motion planning, effectively avoiding collisions between the picking robot and obstacles during picking process, and improving the success rate of picking.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Robotics
Chinmaya Sahu, Dayal R. Parhi, Priyadarshi Biplab Kumar, Manoj Kumar Muni, Animesh Chhotray, Krishna Kant Pandey
Summary: In this research, kinematic analysis of a humanoid NAO robot is attempted using both the DH parameter approach and the multibody formulation approach. The robot is solved by separating it into five individual kinematic chains in the DH parameter approach, while in the multibody formulation approach, it is divided into 15 segments. The data obtained from kinematic analysis can be used for real-time path planning and robot navigation design.
Article
Robotics
Wolfgang Wiedmeyer, Philipp Altoe, Jonathan Auberle, Christoph Ledermann, Torsten Kroger
Summary: The paper introduces a closed-form inverse kinematics solution based on a multi-objective real-time optimization method, which minimizes joint velocities and accelerations while avoiding joint limits. Compared to traditional methods, it achieves faster motion times and smoother arm motions along Cartesian paths.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Mohamed Slim, Nizar Rokbani, Bilel Neji, Mohamed Ali Terres, Taha Beyrouthy
Summary: This paper proposes a Bat-based meta-heuristic algorithm, called IK-BA, for the inverse kinematics problem of a robotic arm. It shows the effectiveness of IK-BA for single point IK planning and geometric path planning, with potential industrial applications.
Article
Computer Science, Artificial Intelligence
Ju Dai, Hao Li, Rui Zeng, Junxuan Bai, Feng Zhou, Junjun Pan
Summary: Recent studies have made significant progress in 3D human motion prediction, but they mainly describe motion using kinematic knowledge, failing to reveal the physical characteristics of human motion. In this paper, we propose a Kinematic and Dynamic coupled transFormer (KD-Former) that combines dynamics with kinematics to learn powerful features for high-fidelity motion prediction. We formulate a reduced-order dynamic model of the human body to calculate joint forces and construct a non-autoregressive encoder-decoder framework based on the transformer structure. Experimental results on Hu-man3.6M and CMU MoCap benchmarks demonstrate the effectiveness and superiority of our method.
PATTERN RECOGNITION
(2023)
Article
Robotics
Christian Schumacher, Espen Knoop, Moritz Bacher
Summary: This letter presents a versatile Inverse Kinematics (IK) formulation for robots with kinematic loops, allowing precise control over end-effectors and the Center of Mass of slowly walking robots. By introducing a regularizer to avoid kinematic singularities, the formulation demonstrates versatility and efficacy on overactuated systems with loops.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Amirhossein Kazemipour, Maram Khatib, Khaled Al Khudir, Claudio Gaz, Alessandro De Luca
Summary: We present a generalized algorithm for task control of redundant robots that handles hard constraints in both joint and Cartesian space. The algorithm treats these constraints equally and allows for online variations. Simulation and experimental results demonstrate the effectiveness of the approach.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Ricard Bordalba, Lluis Ros, Josep M. Porta
Summary: Kinodynamic rapidly-exploring random tree (RRT) planners are effective tools for finding feasible trajectories in robotic systems, but face challenges when applied to systems with closed-kinematic chains. This article proposes a kinodynamic RRT planner that constructs an atlas of the state space incrementally to address these challenges and demonstrates its performance in complex tasks.
IEEE TRANSACTIONS ON ROBOTICS
(2021)
Article
Engineering, Aerospace
B. Naveen, Suril V. Shah, Arun K. Misra
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
(2019)
Article
Robotics
Ajinkya Bhole, Sri Harsha Turlapati, V. S. Rajashekhar, Jay Dixit, Suril Shah, K. Madhava Krishna
Article
Mathematical & Computational Biology
Hari Teja Kalidindi, Thomas George Thuruthel, Cecilia Laschi, Egidio Falotico
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
(2019)
Article
Computer Science, Interdisciplinary Applications
Anirvan Dutta, Durgesh Haribhau Salunkhe, Shivesh Kumar, Arun Dayal Udai, Suril Shah
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2019)
Article
Engineering, Multidisciplinary
Hari Teja Kalidindi, Lorenzo Vannucci, Cecilia Laschi, Egidio Falotico
Summary: This study presents a cerebellum-inspired adaptive filter model that can simultaneously improve accuracy and movement-time, implemented and validated on a humanoid robot. The research found separate plasticity mechanisms in the model cerebellum that control accuracy and movement-time, ensuring optimal saccades are produced by receiving end reaching error direction as an evaluative signal. The model also emulates movement kinematics encoding observed in biological experiments.
BIOINSPIRATION & BIOMIMETICS
(2021)
Article
Engineering, Aerospace
Deepak Raina, Sunil Gora, Dheeraj Maheshwari, Suril Shah
Summary: This paper provides a unified framework for simulating the dynamics, stabilization, and control of a multi-arm space robot system capturing orbiting objects. The framework models the three phases of the capturing operation using impulse-momentum approach and conservation of momentum, and employs a reactionless control strategy to maneuver the robot arms and target object during post-impact phase.
Article
Biology
Hari Teja Kalidindi, Kevin P. Cross, Timothy P. Lillicrap, Mohsen Omrani, Egidio Falotico, Philip N. Sabes, Stephen H. Scott
Summary: Recent studies have shown that rotational dynamics in the motor cortex (MC) may not only be due to intrinsic connections, but also influenced by continuous sensory feedback and interactions with other brain areas. By building and training neural networks, it was revealed that rotational structure exists in both MC and somatosensory cortex.
Article
Robotics
Francesco Pique, Hari Teja Kalidindi, Lorenzo Fruzzetti, Cecilia Laschi, Arianna Menciassi, Egidio Falotico
Summary: Learning-based modeling and control have advantages in soft robot applications due to the neural network's ability to capture complex dynamics with low computational cost. Continual Learning techniques, such as elastic weight consolidation, allow networks to continuously learn from available data without catastrophic forgetting, which can be beneficial in adapting to changing dynamics and improving control performance in soft robots.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Biochemical Research Methods
Lorenzo Fruzzetti, Hari Teja Kalidindi, Alberto Antonietti, Cristiano Alessandro, Alice Geminiani, Claudia Casellato, Egidio Falotico, Egidio D'Angelo
Summary: Saccadic eye movements are crucial for visuo-motor control, but the neural processes governing saccades adaptation are not fully understood. In this study, a model of the saccadic system was reconstructed to explore the synaptic and neural circuit mechanisms underlying predictive saccadic control. The results reveal the roles of long-term potentiation and depression in regulating saccadic kinematics and improving overall quality.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Proceedings Paper
Automation & Control Systems
Rahul Tallamraju, Durgesh H. Salunkhe, Sujit Rajappa, Aamir Ahmad, Kamalakar Karlapalem, Suril Shah
2019 IEEE 15TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Rahul Tallamraju, Venkatesh Sripada, Suril Vijaykumar Shah
2019 28TH IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (RO-MAN)
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
D. Raina, P. Mithun, S. V. Shah, S. Kumar
2019 28TH IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (RO-MAN)
(2019)
Proceedings Paper
Engineering, Mechanical
Deepak Raina, Sunil Gora, Suril Vijaykumar Shah
MACHINES, MECHANISM AND ROBOTICS
(2019)
Article
Automation & Control Systems
Runwei Guan, Shanliang Yao, Lulu Liu, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee, Yutao Yue
Summary: With the development of Unmanned Surface Vehicles (USVs), the perception of inland waterways has become significant. Traditional RGB cameras cannot work effectively in adverse weather and at night, which has led to the emergence of 4D millimeter-wave radar as a new perception sensor. However, the radar suffers from water-surface clutter and irregular shape of point cloud. To address these issues, this paper proposes a high-performance panoptic perception model called Mask-VRDet, which fuses features of vision and radar using graph neural network.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Adrien Le Reun, Kevin Subrin, Anthony Dubois, Sebastien Garnier
Summary: This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Weiming Ba, Jung-Che Chang, Jing Liu, Xi Wang, Xin Dong, Dragos Axinte
Summary: This paper proposes a hybrid scheme for kinematic control of continuum robots, which avoids errors through tension supervision and accurate piecewise linear approximation. The effectiveness of the controller is verified on different continuum robotic systems.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Celiktutan, Antonio Paolillo
Summary: In this study, a learning-based approach is proposed to predict the probability of human users interacting with a robot before the interaction begins. By considering the pose and motion of the user, the approach labels the robot's encounters with humans in a self-supervised manner. The method is validated and deployed in various scenarios, achieving high accuracy in predicting user intentions to interact with the robot.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Tiago Cortinhal, Eren Erdal Aksoy
Summary: This work presents a new depth-and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation between LiDAR and camera sensors. The model is able to translate raw LiDAR point clouds to RGB-D camera images by solely relying on semantic scene segments, and it has practical applications in fields like autonomous vehicles.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Marios Krestenitis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Konstantinos Ioannidis, Elias B. Kosmatopoulos, Stefanos Vrochidis
Summary: This paper addresses the issue of informative path planning for a UAV used in precision agriculture. By using a non-uniform scanning approach, the time spent in areas with minimal value is reduced, while maintaining high precision in information-dense regions. A novel active sensing and deep learning-based coverage path planning approach is proposed, which adjusts the UAV's speed based on the quantity and confidence level of identified plant classes.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shota Kokubu, Pablo E. Tortos Vinocour, Wenwei Yu
Summary: In this study, a new modular soft actuator was proposed to improve the support performance of soft rehabilitation gloves (SRGs). Objective evaluations and clinical tests were conducted to demonstrate the effectiveness and functionality of the proposed actuator and SRG.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Jinliang Zhu, Yuanxi Sun, Jie Xiong, Yiyang Liu, Jia Zheng, Long Bai
Summary: This paper proposes an active prosthetic knee joint with a variable stiffness parallel elastic actuation mechanism. Numerical verifications and practical experiments demonstrate that the mechanism can reduce torque and power, thus reducing energy consumption and improving the endurance of the prosthetic knee joint.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Yong You, Jingtao Wu, Yunlong Meng, Dongye Sun, Datong Qin
Summary: A new power-cycling variable transmission (PCVT) is proposed and applied to construction vehicles to improve transmission efficiency. A shift correction strategy is developed based on identifying the changes in construction vehicles' mass and gradient. Simulation results show that the proposed method can correct shift points, improve operation efficiency, and ensure a safer operation process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaorui Liu, Wei Tian, Jianxin Shen, Bo Li, Pengcheng Li
Summary: This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pengchao Ding, Faben Zhu, Hongbiao Zhu, Gongcheng Wang, Hua Bai, Han Wang, Dongmei Wu, Zhijiang Du, Weidong Wang
Summary: We propose an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme includes stair localization, structural parameter estimation, and optimization of the approaching process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pedro Azevedo, Vitor Santos
Summary: Accurate detection and tracking of vulnerable road users and traffic objects are vital tasks for autonomous driving and driving assistance systems. This paper proposes a solution for object detection and tracking in an autonomous driving scenario, comparing different object detectors and exploring the deployment on edge devices. The effectiveness of DeepStream technology and different object trackers is assessed using the KITTI tracking dataset.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Benjamin Beiter, Divya Srinivasan, Alexander Leonessa
Summary: Powered exoskeletons can significantly reduce physical workload and have great potential impact on future labor practices. To truly assist users in achieving task goals, a shared autonomy control framework is proposed to separate the control objectives of the human and exoskeleton. Positive Power control is introduced for the human-based controller, while 'acceptance' is used as a measure of matching the exoskeleton's control objective to the human's. Both control objectives are implemented in an optimization-based Whole-Body-Control structure. The results verify the effectiveness of the control framework and its potential for improving cooperative control for powered exoskeletons.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
