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IEEE International Conference on robotics and Automation

作者： Selim Ozel Erik H. Skorina Ming Luo Weijia Tao Fuchen Chen Yixiao Pan Cagdas D. Onal Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute MA 01609 USA

ISBN: (纸本)9781467380270

Soft robotics carries the promise of making robots as capable and adaptable as biological creatures, but this will not be possible without the ability to perform self-sensing and control with precision and repeatability. In this paper, we seek to address this need with the development of a new pneumatically-actuated soft bending actuation module with integrated curvature sensing. We designed and fabricated two different versions of this module: One with a commercially available resistive flex sensor and the other with a magnetic curvature sensor of our own design, and used an external motion capture system to calibrate and validate these two approaches. In addition, we used an iterative sliding mode controller to drive the modules through step curvature references to demonstrate the controllability of the modules as well as compare the usability of the two sensors. We found that the magnetic sensor returned noisy but accurate data, while the flex sensor had minor inaccuracies and it was subject to overshoot but did not exhibit notable noise. Experimental results show that this phenomenon of overshoot from the flex sensor causes active feedback control of the bending actuator to exhibit significant positioning errors. This work demonstrates that our soft bending actuator can be controlled with repeatability and precision, and that our magnetic curvature sensor represents an improvement for use in proprioception and closed-loop control of soft robotic devices.

关键词： Module Integrated Curvature

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Motion Control of a Soft-Actuated Modular Manipulator

Motion Control of a Soft-Actuated Modular Manipulator

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IEEE International Conference on robotics and Automation

作者： Erik H. Skorina Weijia Tao Fuchen Chen Ming Luo Cagdas D. Onal Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute MA 01609 USA

ISBN: (纸本)9781467380270

Soft pneumatic actuators can allow robotic manipulators to interact safely in complex environments in close proximity to humans, but work still needs to be done controlling them more effectively. We explore this area by introducing a 2-degree of freedom (DoF) universal joint module actuated by three reverse Pneumatic Artificial Muscles (rPAMs) and an associated geometric Jacobian-enhanced iterative sliding mode controller. After demonstrating the effectiveness of this controller, we combine two of these modules to form a 4-DoF soft actuated manipulator. To control this modular manipulation system, we propose two controllers: a direct inverse kinematic (IK) controller and an end-effector geometric Jacobian controller. Though both controllers were validated to function effectively, the Jacobian controller was more precise (especially under payload) while the IK controller was more accurate.

关键词： Control Soft-Actuated Modular

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Cognitive TransFuser: Semantics-Guided Transformer-Based Sensor Fusion for Improved Waypoint Prediction 11th

Cognitive TransFuser: Semantics-Guided Transformer-Based Sen...

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11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023

作者： Choi, Hwan-Soo Jeong, Jongoh Hoo Cho, Young Yoon, Kuk-Jin Kim, Jong-Hwan Robot Intelligence Technology Lab. School of Engineering KAIST Daejeon Korea Republic of dSPECTER Seoul Korea Republic of Visual Intelligence Lab. Robotics Program and Dept. of Mechanical Engineering KAIST Daejeon Korea Republic of

ISBN: (纸本)9783031706868

Sensor fusion approaches for intelligent self-driving agents remain key to driving scene understanding given visual global contexts acquired from input sensors. Specifically, for the local waypoint prediction task, single-modality networks are still limited by strong dependency on the sensitivity of the input sensor, and thus recent works therefore promote the use of multiple sensors in fusion in feature level in practice. While it is well known that multiple data modalities encourage mutual contextual exchange, it requires global 3D scene understanding in real-time with minimal computation upon deployment to practical driving scenarios, thereby placing greater significance on the training strategy given a limited number of practically usable sensors. In this light, we exploit carefully selected auxiliary tasks that are highly correlated with the target task of interest (e.g., traffic light recognition and semantic segmentation) by fusing auxiliary task features and also using auxiliary heads for waypoint prediction based on imitation learning. Our RGB-LIDAR-based multi-task feature fusion network, coined Cognitive TransFuser, augments and exceeds the baseline network by a significant margin for safer and more complete road navigation in the CARLA simulator. We validate the proposed network on the Town05 Short and Town05 Long Benchmark through extensive experiments, achieving up to 44.2 FPS real-time inference time. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Semantic Segmentation

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Approximate Dynamic programming with Probabilistic Temporal Logic Constraints

Approximate Dynamic Programming with Probabilistic Temporal ...

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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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A Design for Improvement of Visual SLAM in Dynamic Environments Using Feature-Point Removal of Moving Persons

A Design for Improvement of Visual SLAM in Dynamic Environme...

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2023 International Automatic Control Conference, CACS 2023

作者： Song, Kai-Tai Meng, Ching-Hao National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering Hsinchu886-3-5731865 Taiwan National Yang Ming Chiao Tung University Graduate Degree Program of Robotics College of Engineering Hsinchu Taiwan

ISBN: (纸本)9798350306354

This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization accuracy of a mobile robot in an environment with moving persons. Instance segmentation and motion tracking are intergrated to identify motion state of people in an image. ORB feature points belonging to moving persons are removed for further processing of the vSLAM pipeline. The advantage of this method is that the vSLAM can remove feature points of moving people, while retain those belonging to static people in the environment, which improves the accuracy of robot pose estimation. The improved ORB-SLAM2 algorithm has been implemented in a NVIDIA Xavier embedded system, which is integrated to a mobile robot. In practical robot navigation experiments, the average positioning error of the proposed method is within 4cm for 22.4m travel distance. Compared with conventional ORB-SLAM2, the average accuracy of our vSLAM method improves 97% in a dynamic environment with moving people. © 2023 IEEE.

关键词： Mobile robots

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Obstacle recognition using a haptic device

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Journal of Measurement Science and Instrumentation 2013年第4期4卷 376-380页

作者： Kyungwook Noh Donghyuk Lee Sunkyun Kang Jaewon An Jangmyung Lee Department of Interdisciplinary Program in Robotics Pusan National University Department of Electrical Engineering Pusan National University

A haptic device is proposed which gives the user feedback information on their location and orientation of the obstacle through the mobile robot that detects the obstacle in an environment where the user cannot *** robot recognizes the exact position of the obstacle through configuring the nested ultrasonic sensor and giving feedback information to the haptic *** haptic device consisting of five vibration motors can realize the haptic through the vibration of user's finger using the position information of the obstacle received *** addition,it has high accuracy to recognize the surrounding environment and realizes the various situations with the fuzzy controller and the nested ultrasonic sensors.

关键词： haptic device teleoperation haptic feedback mobile robot obstacle recognitionDocument code：AArticle ID：1674-8042（2013）04-0376-05

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Applying CNN Models with Stereo Camera for Object Detection and Distance Estimation in Automatic Micro Electric Vehicle (MEVi) 1

Applying CNN Models with Stereo Camera for Object Detection ...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Harimanto, Farrell Putra Hasanah, Nurul Pradana, Muhammad Khristamto Aditya Puji, Muhammad Nurul Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia National Research and Innovation Agency Kst Samaun Samadikun Research Center for Smart Mechatronics Bandung40135 Indonesia

ISBN: (纸本)9798350368918

Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as it can accurately estimate the distance to the detected objects. In current developments technologies such as stereo cameras are more popular for a more accurate depth estimation. The process for object detection consists of a combination of classification, localization, and segmentation. Deep convolutional neural networks are the basis of object detection. The methods for object detection are divided into two categories namely the Region Proposal-based method such as RCNN, and the Classification-based method which provides for methods such as YOLO and MobileNet. As a part of the research conducted by the National Research and Innovation Agency (BRIN) on Automatic Micro Electric Vehicles or MEVi, this paper analyzed and compared the performance of several CNN models for object detection as well as the performance of depth sensing using ZED stereo camera which was used for the autonomous system in MEVi. Among several models that had been compared, YOLO v8 model demonstrates high accuracy and moderate speed as indicated by its high mAP (0.50) and FPS (38.46). Based on depth sensing results, the accuracy of distance measurement also depended on brightness and environment with the average of accuracy achieved indoors was 98.2% and outdoors was 96.3%. © 2024 IEEE.

关键词： Automotive industry

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Computational Analysis of Mechanical Interactions between a Soft Robotic Device and a Skin-Muscle Phantom for Mechanotherapy 46

Computational Analysis of Mechanical Interactions between a ...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Ticllacuri, Victor Mio, Renato Biomedical Engineering Program PUCP-UPCH Lima Peru Pontificia Universidad Catolica del Peru Laboratory of Biomechanics and Applied Robotics Lima Peru Universidad Peruana Cayetano Heredia Laboratory of Biomedical Engineering Lima Peru University of Bayreuth Germany

ISBN: (纸本)9798350371499

Studying the soft robot-tissue mechanical interaction in muscle stimulation devices poses a significant challenge due to the complex behavior of the materials involved. To advance this field, this paper models computationally three types of soft elastomeric actuators designed to perform deep cyclic compression stimuli on human soft tissues for muscle rehabilitation by mechanotherapy. The analysis focuses on the interaction between a phantom representing transversely isotropic muscle and homogeneous skin, with a soft robotic device comprised of a hyperelastic actuator and a rigid support. Results from deformation, stress-strain and surface pressure analysis demonstrate efficient actuation, suggesting deep and focused stimulation on the muscle, while actuators exhibit reliable safety factors and load distribution, implying longer operational life. This lightweight and compact soft robotic device is suitable for integration into a wearable suit for targeted muscle groups stimulation in the lower limbs. Furthermore, this computational approach represents a significant advance in the biomechanical study of soft robot-human tissues interaction, with potential for generalization in similar biomedical device applications. Keywords - Soft robotics, Mechanotherapy, Transversely Isotropic Muscle, Human-Robot interaction. © 2024 IEEE.

关键词： Phantoms

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Scalar field reconstruction based on the Gaussian process and adaptive sampling

Scalar field reconstruction based on the Gaussian process an...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Porsteinn B. Jónsson Jeonghyeon Wang Jinwhan Kim Mobile Robotics and Intelligence (MORIN) Laboratory Departrnent of Mechanical Engineering KAIST Daeieon Korea Robotics Program KAIST Daejeon Korea

This paper proposes a method of reconstructing a scalar field by adaptively choosing sampling locations and using the measurements obtained from those locations to reconstruct an estimate of the underlying field using Gaussian process regression. Spreading sampling points evenly over the field may not always be effective if the field is not uniformly distributed and the maximum number of measurements is limited. Taking more measurements in regions of large changes in the field than in regions of small changes can give a better estimate than spreading the same number of measurements evenly over the space. The proposed algorithm was tested on a synthetic scalar field and compared to two popular methods of determining sensor placement based on entropy and mutual information from information theory.

关键词： Entropy Mutual information Gaussian processes Training Covariance matrices Training data Simulated annealing

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Probabilistic voxel mapping using stereo matching confidence

Probabilistic voxel mapping using stereo matching confidence

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2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2011

作者： Kim, Sijong Ahn, Seunguk Chung, Myung Jin Department of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon 305-701 Korea Republic of Robotics Program Korea Advanced Institute of Science and Technology Daejeon 305-701 Korea Republic of

ISBN: (纸本)9781457707223

There has been meaningful research into the development of 3D world modeling techniques that are important requisite for intelligent vehicle navigation. In this paper we describe a 3D probabilistic voxel mapping process using stereo matching confidence. Proposed 3D probabilistic voxel map is more reliable representation than general voxel map that just contains the occupancy information. To get the matching confidence value, we evaluate stereo matching costs and its propagation. We test the proposed method in large-scale outdoor environment. © 2011 IEEE.

关键词： Intelligent vehicle highway systems

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