Vision-Based Control of a Mobile Manipulator With an Adaptable-Passive Suspension for Unstructured Environments

Cárdenas, Antonio; Quiroz, Osmar; Hernandez, Ricardo Antonio Parrao; Medellín-Castillo, Hugo I.; González, Alejandro; Maya, Mauro; Piovesan, Davide

doi:10.1115/1.4051437

Cited by 3 publications

(1 citation statement)

References 54 publications

(79 reference statements)

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“…This method of target tracking is called active object tracking (AOT) (Li et al, 2020; Luo et al, 2018). However, current research on AOT is mainly focused on mobile robots (Cardenas et al, 2021; Cortés-Pérez and Torres-Méndez, 2021; Deutsch et al, 2005; Luo et al, 2019; Xi et al, 2021) or unmanned vehicles (Chang et al, 2020; Dong et al, 2021; Lin et al, 2022). Due to the widespread usage of space manipulators and the importance of AOT in non-cooperative target relative tasks, this article will investigate the active non-cooperative target tracking of FFSM.…”

Section: Introductionmentioning

confidence: 99%

End-to-end active non-cooperative target tracking of free-floating space manipulators

Lei

2023

Transactions of the Institute of Measurement and Control

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Active non-cooperative target tracking is an important ability for free-floating space manipulator (FFSM) systems. Aiming at the difficulty of pose and posture estimation of non-cooperative targets and the complexity of FFSM planning and control, the paper proposed an end-to-end target tracking algorithm using deep reinforcement learning (DRL) algorithm. The algorithm uses raw camera images as input and directly outputs the manipulator joint velocities. To deal with the partially observable Markov decision processes (POMDP) problem caused by single image input, we combine the soft actor–critic algorithm with recurrent neural networks. Therefore, the velocity information of the target is introduced to transform the task into a fully observable Markov decision-making process (MDP). Our approach is completely data-driven. It avoids the position and posture estimation of non-cooperative target and the complex modeling motion planning process of FFSM. We trained and tested the algorithm by building a simulation environment in CoppeliaSim. The results showed that our approach achieved good results in active non-cooperative target tracking of FFSM systems and demonstrated the great potential of DRL algorithms in solving space tasks.

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Section: Introductionmentioning

confidence: 99%

End-to-end active non-cooperative target tracking of free-floating space manipulators

Lei

2023

Transactions of the Institute of Measurement and Control

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A Survey of Wheeled Mobile Manipulation: A Decision-Making Perspective

Thakar

Srinivasan

Al-Hussaini

et al. 2022

Journal of Mechanisms and Robotics

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Mobile manipulators that combine base mobility with the dexterity of an articulated manipulator have gained popularity in numerous application verticals ranging from manufacturing, infrastructure inspection to domestic-service applications. Deployments span a range of information- and physical-level interaction tasks with the operational environment, from inspection to tending and logistics-resupply to assembly. Flexible decision-support methodologies and frameworks are crucial for successful mobile manipulation in (semi-) autonomous and teleoperation contexts. However, given the enormous scope of the literature, we restrict our attention to decision-support frameworks specifically in the context of wheeled mobile manipulation. Any discussion of decision-support methodologies/frameworks is intimately tied to the underlying design architectures, planning-control frameworks, and the human-robot interactions. Design architectures offer the primordial cyber-physical substrate upon which deliberative (i.e., planning), reactive (i.e., control), and human-robot interaction-based decision making can exhibit intelligent behavior. These three aspects are inextricably interwoven into and influence all aspects of task performance and application deployments. Hence, we present a classification of wheeled mobile manipulation literature while accounting for the diversity as well as the intertwining of deployment tasks, application-arenas, and decision-making methodologies for mobile manipulation with an eye for future avenues for research.

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Autonomous Cricothyroid Membrane Detection and Manipulation Using Neural Networks and a Robot Arm for First-Aid Airway Management

Han

Ren

et al. 2023

Journal of Medical Devices

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Cricothyrotomy serves as one of the most efficient surgical interventions when a patient is enduring a Can't Intubate Can't Oxygenate (CICO) scenario. However, medical background and professional training are required for the provider to establish a patent airway successfully. Motivated by robotics applications in search and rescue, this work focuses on applying artificial intelligence techniques on the precise localization of the incision site, the cricothyroid membrane (CTM), of the injured using an RGB-D camera, and the manipulation of a robot arm with reinforcement learning to reach the detected CTM keypoint. In this paper, we further improved the success rate of our previously proposed Hybrid Neural Network (HNNet) in detecting the CTM from 84.3% to 96.6%, yielding an error of less than 5mm in real-world coordinates. In addition, a separate neural network was trained to manipulate a robotic arm for reaching a waypoint with an error of less than 5mm. An integrated system that combines both the perception and the control techniques was built and experimentally validated using a human-size manikin to validate the overall concept of autonomous cricothyrotomy with an RGB-D camera and a robotic manipulator using artificial intelligence.

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Vision-Based Control of a Mobile Manipulator With an Adaptable-Passive Suspension for Unstructured Environments

Cited by 3 publications

References 54 publications

End-to-end active non-cooperative target tracking of free-floating space manipulators

End-to-end active non-cooperative target tracking of free-floating space manipulators

A Survey of Wheeled Mobile Manipulation: A Decision-Making Perspective

Autonomous Cricothyroid Membrane Detection and Manipulation Using Neural Networks and a Robot Arm for First-Aid Airway Management

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