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检索条件"任意字段=International Symposium on Computational Intelligence in Robotics and Automation"

共 3103 条记录，以下是491-500 订阅

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Online DCM Trajectory Adaptation for Push and Stumble Recovery during Humanoid Locomotion

Online DCM Trajectory Adaptation for Push and Stumble Recove...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Mesesan, George Englsberger, Johannes Ott, Christian German Aerosp Ctr DLR Inst Robot & Mechatron Wessling Germany

ISBN: (纸本)9781728190778

In this paper, we present a highly efficient Divergent Component of Motion (DCM) reference trajectory generator capable of adapting online to large perturbations acting on the center-of-mass (push recovery) and on the swing foot (stumble recovery). For push recovery, we propose an analytic solution for a footstep adjustment strategy based on the DCM dynamics. The proposed algorithm considers double support phases explicitly and is active throughout the motion, i.e., during both single and double support phases. For stumble recovery, we introduce a continuous DCM trajectory adaptation based on the instantaneous tracking error of the swing foot. Our method is highly efficient, computing a push recovery solution within 10 microseconds on the robot hardware. Furthermore, it achieves robust locomotion for large external perturbations, which we demonstrate in simulations and experiments with the humanoid robot TORO.

关键词： Tracking Perturbation methods Heuristic algorithms Conferences computational modeling Dynamics Humanoid robots

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Mass Estimation of a Moving Object Through Minimal Manipulation Interaction

Mass Estimation of a Moving Object Through Minimal Manipulat...

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IEEE international Conference on robotics and automation (ICRA)

作者： Aguilera, Sergio Murtaza, Muhammad Ali Zhao, Ye Hutchinson, Seth Georgia Inst Technol Inst Robot & Intelligent Machines Atlanta GA 30332 USA

ISBN: (纸本)9781728190778

In this paper, we study the problem of dynamic interaction between a robot and an unknown object (e.g., catching a ball, or handing off an object during locomotion). In particular, we propose a method for estimating the inertial parameters of an object during dynamic interaction, while minimally altering the trajectory of the object - a minimal interaction approach. Our method combines trajectory estimation (e.g., using standard methods from computer vision) with a model-based estimator that exploits the robot's known dynamic model. We first develop the method for a generalized three-dimensional problem, and then evaluate the method for the case of an object moving along a linear trajectory. We present experimental results obtained using a KUKA iiwa 7 interacting with rolling balls of varying mass. Our experiments demonstrate that the mass of the objects can be accurately estimated at the moment of impact when accurate object trajectory estimates are available, and that significant improvement can be obtained by incorporating force measurements at the contact point while following the object.

关键词： Computer vision Force measurement computational modeling Conferences Estimation Manipulators Trajectory

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Voxel Mamba: group-free state space models for point cloud based 3D object detection 24

Voxel Mamba: group-free state space models for point cloud b...

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Proceedings of the 38th international Conference on Neural Information Processing Systems

作者： Guowen Zhang Lue Fan Chenhang He Zhen Lei Zhaoxiang Zhang Lei Zhang The Hong Kong Polytechnic University and Centre for Artificial Intelligence and Robotics HKISI CAS Institute of Automation Chinese Academy of Sciences The Hong Kong Polytechnic University Centre for Artificial Intelligence and Robotics HKISI CAS and Institute of Automation Chinese Academy of Sciences and School of Artificial Intelligence University of Chinese Academy of Sciences

ISBN: (纸本)9798331314385

Serialization-based methods, which serialize the 3D voxels and group them into multiple sequences before inputting to Transformers, have demonstrated their effectiveness in 3D object detection. However, serializing 3D voxels into 1D sequences will inevitably sacrifice the voxel spatial proximity. Such an issue is hard to be addressed by enlarging the group size with existing serialization-based methods due to the quadratic complexity of Transformers with feature sizes. Inspired by the recent advances of state space models (SSMs), we present a Voxel SSM, termed as Voxel Mamba, which employs a group-free strategy to serialize the whole space of voxels into a single sequence. The linear complexity of SSMs encourages our group-free design, alleviating the loss of spatial proximity of voxels. To further enhance the spatial proximity, we propose a Dual-scale SSM Block to establish a hierarchical structure, enabling a larger receptive field in the 1D serialization curve, as well as more complete local regions in 3D space. Moreover, we implicitly apply window partition under the group-free framework by positional encoding, which further enhances spatial proximity by encoding voxel positional information. Our experiments on Waymo Open Dataset and nuScenes dataset show that Voxel Mamba not only achieves higher accuracy than state-of-the-art methods, but also demonstrates significant advantages in computational efficiency. The source code is available at https://***/gwenzhang/Voxel-Mamba.

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Continuous Shortest Path Vector Field Navigation on 3D Triangular Meshes for Mobile Robots

Continuous Shortest Path Vector Field Navigation on 3D Trian...

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IEEE international Conference on robotics and automation (ICRA)

作者： Puetz, Sebastian Wiemann, Thomas Piening, Malte Kleine Hertzberg, Joachim Osnabruck Univ Inst Comp Sci DFKIKnowledge Based Syst Plan Based Robot ControlGerman Res Ctr Artificia Osnabruck Germany

ISBN: (纸本)9781728190778

We present a highly efficient approach to compute continuous shortest path vector fields on arbitrarily shaped 3D triangular meshes for robot navigation in complex real-world outdoor environments. The continuity of the vector field allows to query the shortest distance, direction and geodesic path to the goal at any point within the mesh triangles, resulting in accurate paths. In order to avoid impassable areas, our wavefront propagation method runs on a modular extendable multilayer map architecture taking different geometric cost layers into account. We describe the mathematical foundation of the geodesic distances and continuous vector field computation and demonstrate the performance in real-world and multilevel environments on our campus with a tunnel, ramps and staircases, and in a difficult, steep forest area with a stone quarry. For reproducibility, we provide a ready-to-use ROS software stack as well as Gazebo simulations.

关键词： Three-dimensional displays Runtime Costs Navigation Robot kinematics computational modeling Forestry

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Efficient Recovery of Multi-Camera Motion from Two Affine Correspondences

Efficient Recovery of Multi-Camera Motion from Two Affine Co...

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IEEE international Conference on robotics and automation (ICRA)

作者： Guan, Banglei Zhao, Ji Barath, Daniel Fraundorfer, Friedrich Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha Peoples R China Czech Tech Univ Ctr Machine Percept Prague Czech Republic MTA SZTAKI Machine Percept Res Lab Budapest Hungary Graz Univ Technol Inst Comp Graph & Vis Graz Austria German Aerosp Ctr Remote Sensing Technol Inst Cologne Germany

ISBN: (纸本)9781728190778

We propose an efficient method to estimate the relative pose of a multi-camera system from a minimum of two affine correspondences (ACs). Our solution is novel as it computes the 6DOF relative pose by utilizing a first-order rotation approximation. We directly derive a single polynomial based on the constraint between ACs and the generalized camera model. Then a closed-form solution is found analytically and it produces an accurate relative pose estimation efficiently. Benefiting from the low number of exploited correspondences and the speed of the solver, it speeds up robust estimators, e.g. RANSAC, significantly. The proposed method is evaluated both on synthetic data and real-world image sequences from the KITTI benchmark. It is shown that the proposed solver is superior to the state-of-the-art algorithms in terms of accuracy.

关键词： Closed-form solutions automation computational modeling Roads Conferences Pose estimation Benchmark testing

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Ellipse Loss for Scene-Compliant Motion Prediction

Ellipse Loss for Scene-Compliant Motion Prediction

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IEEE international Conference on robotics and automation (ICRA)

作者： Cui, Henggang Shajari, Hoda Yalamanchi, Sai Djuric, Nemanja Uber Adv Technol Grp ATG 50 33rd St Pittsburgh PA 15201 USA Univ Florida Gainesville FL 32611 USA Uber ATG Pittsburgh PA USA

ISBN: (纸本)9781728190778

Motion prediction is a critical part of self-driving technology, responsible for inferring future behavior of traffic actors in autonomous vehicle's surroundings. In order to ensure safe and efficient operations, prediction models need to output accurate trajectories that obey the map constraints. In this paper, we address this task and propose a novel ellipse loss that allows the models to better reason about scene compliance and predict more realistic trajectories. Ellipse loss penalizes off-road predictions directly in a supervised manner, by projecting the output trajectories into the top-down map frame using a differentiable trajectory rasterizer module. Moreover, it takes into account actor dimensions and orientation, providing more direct training signals to the model. We applied ellipse loss to a recently proposed state-of-the-art joint detection-prediction model to showcase its benefits. Evaluation on large-scale autonomous driving data strongly indicates that the method allows for more accurate and more realistic trajectory predictions.

关键词： Training automation Shape Conferences computational modeling Predictive models Data models

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Hierarchical Planning for Long-Horizon Manipulation with Geometric and Symbolic Scene Graphs

Hierarchical Planning for Long-Horizon Manipulation with Geo...

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IEEE international Conference on robotics and automation (ICRA)

作者： Zhu, Yifeng Tremblay, Jonathan Birchfield, Stan Zhu, Yuke NVIDIA Seattle WA 98105 USA Univ Texas Austin Austin TX 78712 USA

ISBN: (纸本)9781728190778

We present a visually grounded hierarchical planning algorithm for long-horizon manipulation tasks. Our algorithm offers a joint framework of neuro-symbolic task planning and low-level motion generation conditioned on the specified goal. At the core of our approach is a two-level scene graph representation, namely geometric scene graph and symbolic scene graph. This hierarchical representation serves as a structured, object-centric abstraction of manipulation scenes. Our model uses graph neural networks to process these scene graphs for predicting high-level task plans and low-level motions. We demonstrate that our method scales to long-horizon tasks and generalizes well to novel task goals. We validate our method in a kitchen storage task in both physical simulation and the real world. Experiments show that our method achieves over 70% success rate and nearly 90% of subgoal completion rate on the real robot while being four orders of magnitude faster in computation time compared to standard search-based task-and-motion planner.(1)

关键词： Visualization automation Conferences computational modeling Predictive models Graph neural networks Planning

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Scalable Learning of Safety Guarantees for Autonomous Systems using Hamilton-Jacobi Reachability

Scalable Learning of Safety Guarantees for Autonomous System...

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IEEE international Conference on robotics and automation (ICRA)

作者： Herbert, Sylvia Choi, Jason J. Sanjeev, Suvansh Gibson, Marsalis Sreenath, Koushil Tomlin, Claire J.

ISBN: (纸本)9781728190778

Autonomous systems like aircraft and assistive robots often operate in scenarios where guaranteeing safety is critical. Methods like Hamilton-Jacobi reachability can provide guaranteed safe sets and controllers for such systems. However, often these same scenarios have unknown or uncertain environments, system dynamics, or predictions of other agents. As the system is operating, it may learn new knowledge about these uncertainties and should therefore update its safety analysis accordingly. However, work to learn and update safety analysis is limited to small systems of about two dimensions due to the computational complexity of the analysis. In this paper we synthesize several techniques to speed up computation: decomposition, warm-starting, and adaptive grids. Using this new framework we can update safe sets by one or more orders of magnitude faster than prior work, making this technique practical for many realistic systems. We demonstrate our results on simulated 2D and 10D near-hover quadcopters operating in a windy environment.

关键词： Uncertainty automation Autonomous systems System dynamics Conferences Control systems Safety

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A Novel 2-DOF Cable-Driven Flexible Manipulator Driven by Pneumatic Artificial Muscles

A Novel 2-DOF Cable-Driven Flexible Manipulator Driven by Pn...

引用

Artificial intelligence and Intelligent Manufacturing (AIIM), international symposium on

作者： Xiaowei Xie Zili Xu Kai Ru Zhiyang Lin School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798331541729

ISBN: (纸本)9798331541736

Cable-driven flexible manipulators are highly flexible and adapt well to complex, unstructured environments. Existing cable-driven flexible manipulators typically employ motor-driven actuators, which result in reduced inherent compliance and pose significant safety risks during interaction with the environment. To address these challenges, this study proposes a 2-DOF cable-driven flexible manipulator driven by pneumatic artificial muscles, with the aim of enhancing compliance and improving safety during interaction. Given the complexity and numerous internal components of the articulated joint segment, conventional dynamic analysis methods are difficult to apply effectively. To overcome these challenges and improve computational efficiency, an equivalent inverse dynamics model for the articulated joint segment is developed. To further improve trajectory tracking accuracy, a cable-length control algorithm based on “PID + feedforward compensation” is designed. Finally, a trajectory tracking simulation platform for the cable-driven flexible manipulator is constructed, validating the high-precision trajectory tracking performance of the control algorithm and further confirming the accuracy and effectiveness of the equivalent inverse dynamics model.

关键词： Artificial muscles Accuracy Trajectory tracking Heuristic algorithms Simulation computational modeling 2-DOF Safety Steady-state Manipulator dynamics

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Challenges and Opportunities of computational intelligence in Industrial Control System (ICS)

Challenges and Opportunities of Computational Intelligence i...

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IEEE symposium Series on computational intelligence (SSCI)

作者： Sunzida Siddique Mohd Ariful Haque Rakib Hossain Rifat Laxmi Rani Das Sajedul Talukder Syed Bahauddin Alam Kishor Datta Gupta Daffodil International University Dhaka Bangladesh Clark Atlanta University Atlanta GA BRAC University Dhaka Bangladesh Noakhali S&T University Noakhali Bangladesh Southern Illinois University Illinois USA University of Illinois at Urbana-Champaign Illinois USA

Artificial intelligence (AI) is not a fancy term anymore, or not limited to only researchers and academia. AI is currently becoming a part and parcel of our daily life, we are using AI/ intelligent systems by knowing or without knowing. Event product manufacturers are also trying to incorporate AI with their products to make it more preferable to consumers and trying to get the full benefit of using AI in their production and control units even for business decisions. Therefore, In our paper, we give a comprehensive survey of recent advances in computational intelligence in industrial Control Systems and cover many usages of how industrial Control Systems are getting benefits from using computational intelligence. We covered multiple domains like Manufacturing, Energy Management, Transportation, Food and Beverage Industry, and Pharmaceutical Industry, how these industries are utilizing multiple CI-based control systems like Programmable Logic Controllers, Distributed Control Systems, Supervisory Control and Data Acquisition, Industrial automation, and Control Systems, Intelligent Electronic Devices and found benefits in their operations and manufacturing which helping them to focus more in innovation and improvement of their products. We believe that this survey shall be valuable to researchers across academia and industry.

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