A Workspace Limit Approach for Teleoperation Based on Signed Distance Function

Li, Gaofeng; Caponetto, Fernando; Bianco, Edoardo Del; Katsageorgiou, Vasiliki-Maria; Sarakoglou, Ioannis; Tsagarakis, Nikos G.

doi:10.1109/lra.2021.3079810

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…In a heterogeneous mapping system, a situation exists that the teleoperation system cannot work effectively when the mapped position p re exceeds the robot EE reachable space. Therefore, to ensure the effective inverse solution of the slave robot and realize the online adjustment of the teleoperation system, and considering the ideas of Li et al [22], the point on the robot EE reachable space boundary that is nearest to p re will be regarded as the suitable position p r of the robot EE. Then, the joint angle of the robot can be solved and the robot can be controlled continuously.…”

Section: Heterogeneous Mapping Methods Based On Link Pose Constraintmentioning

confidence: 99%

Master-Slave Arm Heterogeneous Mapping With Link Pose Constraint in Teleoperation System

Zhang

Zhai

et al. 2022

IEEE Access

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In order to solve the problem in master-slave heterogeneous teleoperation systems, which is that the inverse solution of robot cannot be achieved when the mapped wrist joint exceeds the reachable space of robot wrist joint, a master-slave heterogeneous mapping method based on link pose constraint is proposed. The link pose constraint means that the position and orientation of robot hand link are the same or similar to that of exoskeleton hand link. In the proposed method, the link pose constraint is used in an exoskeleton-based heterogeneous teleoperation system to realize consistent mapping between the exoskeleton and robot hand link inside wrist joint reachable space, and to realize effective inverse solution and consistent mapping of the end effector (EE) outside the reachable space. A simulation was performed by using the proposed method. The simulation results show that the proposed method can effectively realize the mapping between the exoskeleton and robot in the reachable space of robot EE. The teleoperation experimental setup was constructed by using the developed exoskeleton and an industrial robot, and the verification experiments of the proposed mapping method were performed. The experimental results indicate that the position error of the proposed heterogeneous mapping method is 0.48 mm. The experimental results demonstrate that the proposed mapping method can effectively realize master-slave heterogeneous mapping and realize continuous motion control of the teleoperation system, which satisfies the application requirements of human-robot integration, robot skill enhancement, and robot skill learning.

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Section: Heterogeneous Mapping Methods Based On Link Pose Constraintmentioning

confidence: 99%

Master-Slave Arm Heterogeneous Mapping With Link Pose Constraint in Teleoperation System

Zhang

Zhai

et al. 2022

IEEE Access

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“…The implicit function is a powerful tool for characterizing 3D shapes, which has gained great popularity as such a representation is not limited by fixed topology structure and resolution [12]. With the advent of deep learning models, implicit neural representations parameterized by neural networks have enabled great progress in shape reconstruction, 3D data compression, novel view synthesis, model animation [12], [13], [14], [15]. The commonly-used implicit functions can be categorized into two groups: classification-based occupancy [13] and regression-based signed distance function (SDF) [12].…”

Section: Introductionmentioning

confidence: 99%

PoseSDF: Simultaneous 3D Human Shape Reconstruction and Gait Pose Estimation Using Signed Distance Functions

Yang

Liu

et al. 2022

2022 International Conference on Robotics and Automation (ICRA)

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Vision-based 3D human pose estimation and shape reconstruction play important roles in robot-assisted healthcare monitoring and personal assistance. However, 3D data captured from a single viewpoint always encounter occlusions and exhibit substantial heterogeneity across different views, resulting in significant challenges for both tasks. Extensive approaches have been proposed to perform each task separately, but few of them present a unified solution. In this paper, we propose a novel network based on signed distance functions, namely PoseSDF, to simultaneously reconstruct 3D lower limb shape and estimate gait pose by two dedicated branches. To promote multi-task learning, several strategies are developed to ensure that these two branches leverage the same latent shape code while exchanging information between them. More importantly, an auxiliary RotNet is incorporated into the inference phase, overcoming the inherent limitations of implicit neural functions under cross-view scenarios. Experimental results demonstrate that our proposed PoseSDF can achieve both high-quality shape reconstruction and precise pose estimation, generalizing well on the data from novel views, gait patterns, as well as real-world.

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An MPC-Based Framework for Dynamic Trajectory Re-Planning in Uncertain Environments

Lei

Lü

Laurenzi

et al. 2022

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)

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Modular reconfigurable manipulators enable quick adaptation and versatility to address different application environments and tailor to the specific requirements of the tasks. Task performance significantly depends on the manipulator's mounted pose and morphology design, therefore posing the need of methodologies for selecting suitable modular robot configurations and mounted pose that can address the specific task requirements and required performance. Morphological changes in modular robots can be derived through a discrete optimization process involving the selective addition or removal of modules. In contrast, the adjustment of the mounted pose operates within a continuous space, allowing for smooth and precise alterations in both orientation and position. This work introduces a computational framework that simultaneously optimizes modular manipulators' mounted pose and morphology. The core of the work is that we design a mapping function that implicitly captures the morphological state of manipulators in the continuous space. This transformation function unifies the optimization of mounted pose and morphology within a continuous space. Furthermore, our optimization framework incorporates a array of performance metrics, such as minimum joint effort and maximum manipulability, and considerations for trajectory execution error and physical and safety constraints. To highlight our method's benefits, we compare it with previous methods that framed such problem as a combinatorial optimization problem and demonstrate its practicality in selecting the modular robot configuration for executing a drilling task with the CONCERT modular robotic platform.

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A Workspace Limit Approach for Teleoperation Based on Signed Distance Function

Cited by 6 publications

References 25 publications

Master-Slave Arm Heterogeneous Mapping With Link Pose Constraint in Teleoperation System

Master-Slave Arm Heterogeneous Mapping With Link Pose Constraint in Teleoperation System

PoseSDF: Simultaneous 3D Human Shape Reconstruction and Gait Pose Estimation Using Signed Distance Functions

An MPC-Based Framework for Dynamic Trajectory Re-Planning in Uncertain Environments

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