Article
Robotics
Yuwei Yang, Xiaoyu Wu, Bo Song, Zhijun Li
Summary: This article proposes a whole-body impedance control approach for humanoid wheeled robots, with fuzzy adaptive systems to compensate for the uncertain dynamics of the controlled system. This approach realizes safe interaction and compliant operation with unknown environments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Giulio Romualdi, Stefano Dafarra, Daniele Pucci
Summary: This letter presents a compliant contact model for time-critical humanoid robot motion control, extending traditional linear and rotational springs and dampers used to characterize soft terrains to large contact surface orientations. The model allows computation of equivalent contact force and torque exerted by the environment on the contact surface. The approach is validated through simulation of iCub humanoid robot walking motions and compared with state of the art methods, investigating terrain compliance and robustness to uncertainty in the contact model.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Paolo Maria Viceconte, Raffaello Camoriano, Giulio Romualdi, Diego Ferigo, Stefano Dafarra, Silvio Traversaro, Giuseppe Oriolo, Lorenzo Rosasco, Daniele Pucci
Summary: This letter presents a system architecture that combines computer graphics and robotics methods to generate and stabilize humanoid robot's human-like trajectories. By using human motion capture data, the system generates a general footstep planner and data-driven whole-body postural reference trajectories, increasing the human likeness of the resulting robot motion. Extensive validations with simulations and real experiments on the iCub humanoid robot demonstrate the robustness of the proposed architecture.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Masaki Murooka, Kevin Chappellet, Arnaud Tanguy, Mehdi Benallegue, Iori Kumagai, Mitsuharu Morisawa, Fumio Kanehiro, Abderrahmane Kheddar
Summary: A bipedal control strategy for humanoid loco-manipulation was proposed to account for external forces and compensate for manipulation forces, with pattern generator and stabilizer designed to plan center of mass trajectories and reduce error between desired and actual manipulation forces, showing effectiveness in simulation and real experiments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Stefano Dafarra, Giulio Romualdi, Daniele Pucci
Summary: This article presents a planner that generates walking trajectories for a humanoid robot using centroidal dynamics and full kinematics. The interaction between the robot and the walking surface is explicitly modeled through dynamic complementarity conditions, allowing for automatic generation of footsteps without a predefined contact sequence. The approach addresses the robot control objective through solving an optimal control problem and demonstrates the possibility of achieving automatic walking motions by specifying a minimal set of references. The impact of contact modeling choices on computational time is also analyzed. The approach is validated through generating and testing walking trajectories for the humanoid robot iCub.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Computer Science, Artificial Intelligence
Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone
Summary: Moving in complex environments is crucial for intelligent mobile robots, and researchers and engineers have been dedicated to developing navigation systems to achieve this capability. Recently, there has been a growing interest in applying machine learning techniques, especially deep learning, for motion planning and control in mobile robot navigation. However, there hasn't been much direct comparison between the classical and emerging paradigms in this field. This article surveys recent works that utilize machine learning within the context of classical navigation systems, categorizes them, and identifies common challenges and promising future directions.
Article
Chemistry, Analytical
Mihaela Popescu, Dennis Mronga, Ivan Bergonzani, Shivesh Kumar, Frank Kirchner
Summary: This paper investigates the use of an external motion capture system to provide state feedback to a humanoid robot. Experimental results show the successful application of state-of-the-art motion capture systems in the high-frequency feedback control loop of humanoid robots.
Article
Robotics
Michal Adamkiewicz, Timothy Chen, Adam Caccavale, Rachel Gardner, Preston Culbertson, Jeannette Bohg, Mac Schwager
Summary: The article introduces the use of NeRF for representing 3D scenes, and proposes an algorithm for robot navigation using an RGB camera, including trajectory optimization and pose estimation methods. By combining the trajectory planner with the pose filter in an online replanning loop, a vision-based robot navigation pipeline is established.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Engineering, Mechanical
Jun Li, Haibo Gao, Yuhui Wan, Joseph Humphreys, Christopher Peers, Haitao Yu, Chengxu Zhou
Summary: This paper presents an inverse dynamics-based whole-body controller that can handle locomotion and manipulation tasks simultaneously, considering the coupling effects between them. By using a hierarchical optimization algorithm to track the desired task-space motion, the robot is able to follow multiple tasks successfully.
Article
Computer Science, Information Systems
Emmanuel Ovalle-Magallanes, Noe G. Aldana-Murillo, Juan Gabriel Avina-Cervantes, Jose Ruiz-Pinales, Jonathan Cepeda-Negrete, Sergio Ledesma
Summary: Autonomous robot visual navigation is a fundamental locomotion task that involves extracting relevant features from images taken from the surrounding environment to control independent displacement. This study presents an appearance-based localization method utilizing a visual map and end-to-end Convolutional Neural Network (CNN). By evaluating different pre-trained CNN architectures, such as VGG16 and Xception, it was found that integrating an $L_{2}$ -norm constraint in the training pipeline significantly improved the appearance-based localization performance.
Article
Chemistry, Analytical
Rohit Roy, You-Peng Tu, Long-Jye Sheu, Wei-Hua Chieng, Li-Chuan Tang, Hasan Ismail
Summary: This research proposes the motion control of an indoor mobile robot (IMR) using e-SLAM techniques with limited sensors, specifically only LiDAR. The path is generated from simple floor plans constructed by the IMR exploration. The IMR recognizes its location and environment gradually from the LiDAR data.
Article
Robotics
Masaki Murooka, Mitsuharu Morisawa, Fumio Kanehiro
Summary: This study proposes a trajectory generation and stabilization control method for humanoid dynamic multi-contact motion, which combines preview control, centroidal state feedback, and wrench distribution strategy to achieve stable multi-contact motion.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Diego Ferigo, Raffaello Camoriano, Paolo Maria Viceconte, Daniele Calandriello, Silvio Traversaro, Lorenzo Rosasco, Daniele Pucci
Summary: The study utilizes model-free Deep Reinforcement Learning to train a general and robust humanoid push-recovery policy in a simulation environment, targeting high-dimensional whole-body humanoid control. The incorporation of expert knowledge in reward components enables the policy to quickly learn various robust behaviors, validating its robustness and generalization.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Automation & Control Systems
Lingxuan Zhao, Zhangguo Yu, Lianqiang Han, Xuechao Chen, Xuejian Qiu, Qiang Huang
Summary: Wheeled-legged humanoid robots combine humanoid robot's terrain adaptability and wheeled robot's efficiency. However, stability control in dealing with rough terrains and external disturbances remains unsolved. This research proposes a compliant balance control framework that can absorb shocks, withstand disturbances, and maintain stable motion.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Vikas, Dayal Ramakrushna Parhi, Abhishek Kumar Kashyap
Summary: This study focuses on the optimal path planning of humanoid robots in rugged terrain using a hybrid-based improved gravitational search algorithm (IGSA) tuned with a differentially perturbed velocity (DV) approach. The primary IGSA has drawbacks of lower convergence rate and risk of getting trapped in optimal local conditions, which are eliminated by the hybrid IGSA-DV path planning approach. The algorithm aims to minimize the overall path length of the humanoid from source to goal in minimal time while considering path smoothness and energy efficiency optimization.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Automation & Control Systems
Louis Hawley, Wael Suleiman
ROBOTICS AND AUTONOMOUS SYSTEMS
(2019)
Article
Robotics
Louis Hawley, Remy Rahem, Wael Suleiman
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
(2019)
Article
Computer Science, Artificial Intelligence
Sonny Tarbouriech, Wael Suleiman
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Kevin Dufour, Wael Suleiman
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Christopher Yee Wong, Saeid Samadi, Wael Suleiman, Abderrahmane Kheddar
Summary: Instead of programming robot trajectories, physically manipulating the robot for adjustments is more intuitive and time-saving. This study proposes a set of design rules for generating intuitive touch semantics, allowing for various levels of control from individual joints to whole-body tasks.
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
(2022)
Proceedings Paper
Automation & Control Systems
Christopher Yee Wong, Wael Suleiman
Summary: This paper proposes a preliminary definition and analysis of the sensor observability index, which evaluates the performance of distributed sensors in observing specific axes in task space. The study shows that the sensor observability is more generalizable and avoids false observability singularities compared to traditional kinematic analysis. Simulations and experiments using the robot Baxter demonstrate the importance of maintaining proper sensor observability in physical interactions.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Article
Automation & Control Systems
Kevin Dufour, Jorge Ocampo-Jimenez, Wael Suleiman
ROBOTICS AND AUTONOMOUS SYSTEMS
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Ko Ayusawa, Wael Suleiman, Eiichi Yoshida
2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2019)
Proceedings Paper
Automation & Control Systems
Sonny Tarbouriech, Wael Suleiman
2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
(2018)
Proceedings Paper
Automation & Control Systems
Wael Suleiman, Ko Ayusawa, Fumio Kanehiro, Eiichi Yoshida
2018 IEEE 15TH INTERNATIONAL WORKSHOP ON ADVANCED MOTION CONTROL (AMC)
(2018)
Proceedings Paper
Automation & Control Systems
Kevin Dufour, Wael Suleiman
2018 IEEE 15TH INTERNATIONAL WORKSHOP ON ADVANCED MOTION CONTROL (AMC)
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Louis Hawley, Wael Suleiman
2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Evin Dufour, Wael Suleiman
2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Karen L. Flores-Rodriguez, Felipe Trujillo-Romero, Wael Suleiman
2017 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND COMPUTERS (CONIELECOMP)
(2017)
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)