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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Li, Tingguang Xi, Weitao Fang, Meng Xu, Jia Meng, Max Q.-H. Robotics Perception and AI Laboratory Electronic Engineering Department Chinese University of Hong Kong Hong Kong Tencent AI Lab Shenzhen China

ISBN: (纸本)9781728163215

We present a learning-based approach to solving a Rubik's cube with a multi-fingered dexterous hand. Despite the promising performance of dexterous in-hand manipulation, solving complex tasks which involve multiple steps and diverse internal object structure has remained an important, yet challenging task. In this paper, we tackle this challenge with a hierarchical deep reinforcement learning method, which separates planning and manipulation. A model-based cube solver finds an optimal move sequence for restoring the cube and a model-free cube operator controls all five fingers to execute each move step by step. To train our models, we build a high-fidelity simulator which manipulates a Rubik's Cube, an object containing high-dimensional state space, with a 24-DoF robot hand. Extensive experiments on 1400 randomly scrambled Rubik's cubes demonstrate the effectiveness of our method, achieving an average success rate of 90.3%. To benefit the community, we make our simulator and source code publicly available to advance future research1. © 2019 IEEE.

关键词： Deep learning

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Estimation of surgical tool-tip tracking error distribution in coordinate reference frame involving pivot calibration uncertainty

Estimation of surgical tool-tip tracking error distribution ...

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作者： Min, Zhe Ren, Hongliang Meng, Max Q.-H. Robotics and Perception Laboratory Chinese University of Hong Kong Shatin N.T. Hong Kong Laboratory of Medical Mechatronics National University of Singapore Singapore119077 Singapore

Accurate understanding of surgical tool-tip tracking error is important for decision making in image-guided surgery. In this Letter, the authors present a novel method to estimate/model surgical tool-tip tracking error in which they take pivot calibration uncertainty into consideration. First, a new type of error that is referred to as total target registration error (TTRE) is formally defined in a single-rigid registration. Target localisation error (TLE) in two spaces to be registered is considered in proposed TTRE formulation. With first-order approximation in fiducial localisation error (FLE) or TLE magnitude, TTRE statistics (mean, covariance matrix and root-mean-square (RMS)) are then derived. Second, surgical tool-tip tracking error in optical tracking system (OTS) frame is formulated using TTRE when pivot calibration uncertainty is considered. Finally, TTRE statistics of tool-tip in OTS frame are then propagated relative to a coordinate reference frame (CRF) rigid-body. Monte Carlo simulations are conducted to validate the proposed error model. The percentage passing statistical tests that there is no difference between simulated and theoretical mean and covariance matrix of tool-tip tracking error in CRF space is more than 90% in all test cases. The RMS percentage difference between simulated and theoretical tool-tip tracking error in CRF space is within 5% in all test cases.

关键词： Covariance matrix

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Graph neural network based method for robot path planning

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Biomimetic Intelligence & robotics 2024年第1期4卷 80-87页

作者： Xingrong Diao Wenzheng Chi Jiankun Wang Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical EngineeringSouthern University of Science and TechnologyShenzhen 518055China Robotics and Microsystems Center School of Mechanical and Electric EngineeringSoochow UniversitySuzhou 215021China Jiaxing Research Institute Southern University of Science and TechnologyJiaxing 314000China

Sampling-based path planning is widely used in robotics,particularly in high-dimensional state *** the path planning process,collision detection is the most time-consuming ***,we propose a learning-based path planning method that reduces the number of collision *** develop an efficient neural network model based on graph neural *** model outputs weights for each neighbor based on the obstacle,searched path,and random geometric graph,which are used to guide the planner in avoiding *** evaluate the efficiency of the proposed path planning method through simulated random worlds and real-world *** results demonstrate that the proposed method significantly reduces the number of collision checks and improves the path planning speed in high-dimensional environments.

关键词： Graph Neural Network(GNN) Collision detection Sampling-based path planning

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Recent Developments in Metallic Degradable Micromotors for Biomedical and Environmental Remediation Applications

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Nano-Micro Letters 2024年第3期16卷 1-35页

作者： Sourav Dutta Seungmin Noh Roger Sanchis Gual Xiangzhong Chen Salvador Pané Bradley J.Nelson Hongsoo Choi Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988Republic of Korea DGIST‑ETH Microrobotics Research Center DGISTDaegu 42988Republic of Korea Multi‑Scale Robotics Lab Institute of Robotics and Intelligent SystemsETH Zurich8092 ZurichSwitzerland Institute of Optoelectronics State Key Laboratory of Photovoltaic Science and TechnologyShanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433People’s Republic of China

Synthetic micromotor has gained substantial attention in biomedicine and environmental ***-based degradable micromotor composed of magnesium(Mg),zinc(Zn),and iron(Fe)have promise due to their nontoxic fuel-free propulsion,favorable biocompatibility,and safe excretion of degradation products Recent advances in degradable metallic micromotor have shown their fast movement in complex biological media,efficient cargo delivery and favorable biocompatibility.A noteworthy number of degradable metal-based micromotors employ bubble propulsion,utilizing water as fuel to generate hydrogen *** novel feature has projected degradable metallic micromotors for active in vivo drug delivery *** addition,understanding the degradation mechanism of these micromotors is also a key parameter for their design and *** propulsion efficiency and life span govern the overall performance of a degradable metallic *** we review the design and recent advancements of metallic degradable ***,we describe the controlled degradation,efficient in vivo drug delivery,and built-in acid neutralization capabilities of degradable micromotors with versatile biomedical ***,we discuss micromotors’efficacy in detecting and destroying environmental ***,we address the limitations and future research directions of degradable metallic micromotors.

关键词： Magnesium Zinc Iron Biodegradable microrobot Biomedical Environmental

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Autonomous system for exploration and navigation in drift networks

Autonomous system for exploration and navigation in drift ne...

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IEEE Symposium on Intelligent Vehicle

作者： J.N. Bakambu V. Polotski P. Cohen Perception and Robotics Laboratory Ecole Polytechnique Montreal Canada

This paper describes an autonomous system for exploration and navigation within networks of tunnels, as those typically found in underground mines and caves. In the exploration mode, a remotely located supervisor instructs the system to move through successive sections of the network, gathering range data that is, then, concatenated into 2D/3D survey maps of the environment. In the navigation mode, the supervisor specifies high-level missions on the previously acquired survey maps. A motion planner, then, translates each mission into a set of consecutive navigation actions, separated by natural landmarks. Mission execution consists of detecting landmarks, self-localizing and performing the planned navigation actions.

关键词： Navigation Intelligent networks Laboratories Event detection Concatenated codes Remotely operated vehicles Mobile robots Humans Intelligent systems Artificial intelligence

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Occlusions in obstacle detection for safe navigation

Occlusions in obstacle detection for safe navigation

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IEEE Symposium on Intelligent Vehicle

作者： M. Sadou V. Polotski P. Cohen Perception and Robotics Laboratory École Polytechnique Montreal Canada

Obstacles detection is essential to safe autonomous platform navigation. The obstacle detection methods proposed in the literature do not pay sufficient attention to the occlusion-problem caused by the existence of regions along the trajectory of a vehicle that are hidden by other objects and where potential obstacles might be located. Our approach takes occlusions into account to prevent the possibility of collision. Experimental results with a robotic platform demonstrating the effectiveness of the developed algorithm are presented.

关键词： Radar detection Vehicle detection Robots Remotely operated vehicles Sonar detection Sonar navigation Cameras Laser radar Collision avoidance Laboratories

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Mutual Localization of Mobile Robotic Platforms Using Kalman Filtering

Mutual Localization of Mobile Robotic Platforms Using Kalman...

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Annual Conference of Industrial Electronics Society

作者： Vincent Zalzal Paul Cohen Perception and Robotics Laboratory Ecole Polytechnique de Montreal Montreal QUE Canada Ecole Polytechniquede Montreal Perception and Robotics Laboratory Montreal QUE Canada

The ability of a mobile robotic platform to self-locate within its environment is needed to implement navigation functionalities. In situations where several platforms cooperate to jointly execute tasks, mutual platform localization is paramount to control the robot formation. This paper presents a real-time mutual localization system for multiple mobile platforms. The odometry system of each platform is used to calculate its movement. The updating of the mutual localization uses data sharing between platforms but does not require visual contact between them. An onboard omnidirectional vision system is used for landmark detection. While landmark locations are unknown, their positions within the field of view of the platforms are used for localization error correction, through variable-dimension extended Kalman filtering. The method is fast, robust, and provides accurate results with low-cost equipment

关键词： Mobile robots Kalman filters Robustness Filtering Laboratories Navigation Real time systems Robot kinematics Robot vision systems Cameras

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Real Time Face Detection and Facial Expression Recognition: Development and Applications to Human Computer Interaction

Real Time Face Detection and Facial Expression Recognition: ...

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Conference on Computer Vision and Pattern Recognition Workshop, CVPRW 2003

作者： Bartlett, Marian Stewart Littlewort, Gwen Fasel, Ian Movellan, Javier R. Machine Perception Laboratory Institute for Neural Computation University of California San DiegoCA92093 United States Intelligent Robotics and Communication Laboratories ATR Kyoto Japan

ISBN: (纸本)0769519008

Computer animated agents and robots bring a social dimension to human computer interaction and force us to think in new ways about how computers could be used in daily life. Face to face communication is a real-time process operating at a a time scale in the order of 40 milliseconds. The level of uncertainty at this time scale is considerable, making it necessary for humans and machines to rely on sensory rich perceptual primitives rather than slow symbolic inference processes. In this paper we present progress on one such perceptual primitive. The system automatically detects frontal faces in the video stream and codes them with respect to 7 dimensions in real time: neutral, anger, disgust, fear, joy, sadness, surprise. The face finder employs a cascade of feature detectors trained with boosting techniques [15, 2]. The expression recognizer receives image patches located by the face detector. A Gabor representation of the patch is formed and then processed by a bank of SVM classifiers. A novel combination of Adaboost and SVM's enhances performance. The system was tested on the Cohn-Kanade dataset of posed facial expressions [6]. The generalization performance to new subjects for a 7- way forced choice correct. Most interestingly the outputs of the classifier change smoothly as a function of time, providing a potentially valuable representation to code facial expression dynamics in a fully automatic and unobtrusive manner. The system has been deployed on a wide variety of platforms including Sony's Aibo pet robot, ATR's RoboVie, and CU animator, and is currently being evaluated for applications including automatic reading tutors, assessment of human-robot interaction. © 2003 IEEE.

关键词： Adaptive boosting

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Dynamic Movement Primitives Based Robot Skills Learning

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Machine Intelligence Research 2023年第3期20卷 396-407页

作者： Ling-Huan Kong Wei He Wen-Shi Chen Hui Zhang Yao-Nan Wang School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China School of Robotics and the National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

In this article,a robot skills learning framework is developed,which considers both motion modeling and *** order to enable the robot to learn skills from demonstrations,a learning method called dynamic movement primitives(DMPs)is introduced to model motion.A staged teaching strategy is integrated into DMPs frameworks to enhance the generality such that the complicated tasks can be also performed for multi-joint *** DMP connection method is used to make an accurate and smooth transition in position and velocity space to connect complex motion *** addition,motions are categorized into different goals and *** is worth mentioning that an adaptive neural networks(NNs)control method is proposed to achieve highly accurate trajectory tracking and to ensure the performance of action execution,which is beneficial to the improvement of reliability of the skills learning *** experiment test on the Baxter robot verifies the effectiveness of the proposed method.

关键词： Dynamic movement primitives(DMPs) trajectory tracking control robot learning from demonstrations neural networks(NNs) adaptive control

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Escape strategy for a mobile robot under pursuit

Escape strategy for a mobile robot under pursuit

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IEEE International Conference on Systems, Man and Cybernetics

作者： C. Zanardi J.-Y. Herve P. Cohen Perception and Robotics Laboratory École Polytechnique Montreal QUE Canada

We are addressing here the problem of dynamic interactions between vision-guided mobile robots. We propose here to represent the information about the dynamic capabilities of a robot by a geometric object that we call the dynamic map (DM). We show how the DM can be generated from a dynamic model of a robot and provide an example in the case of a simple car-like vehicle. Finally, a simple planning strategy using this DM is presented.

关键词： Mobile robots Vehicle dynamics Delta modulation Centralized control Intelligent robots Robot vision systems Remotely operated vehicles Collaboration Laboratories Strategic planning

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