Cooperative Manipulation

Caccavale, Fabrizio; Uchiyama, Masaru

doi:10.1007/978-3-319-32552-1_39

Cited by 38 publications

(20 citation statements)

References 54 publications

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“…In this essay, we will refer to multifingered robotic hands. A similar reasoning, however, applies when considering several cooperative manipulators (Caccavale and Uchiyama 2016).…”

Section: Overviewmentioning

confidence: 83%

Dexterous Manipulation

Prattichizzo¹,

Pozzi²,

Malvezzi³

2020

Encyclopedia of Robotics

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“…In this essay, we will refer to multifingered robotic hands. A similar reasoning, however, applies when considering several cooperative manipulators (Caccavale and Uchiyama 2016).…”

Section: Overviewmentioning

confidence: 83%

Dexterous Manipulation

Prattichizzo¹,

Pozzi²,

Malvezzi³

2020

Encyclopedia of Robotics

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“…In order to avoid toppling, the ZMP must lie in the support polygon (SP), namely, the convex hull of the robot's feet. The object wrench h o ∈ R 6 can be obtained in terms of the wrenches applied by the end effectors as follows (Caccavale and Uchiyama, 2016):…”

Section: Static Equilibriummentioning

confidence: 99%

A Holistic Approach to Human-Supervised Humanoid Robot Operations in Extreme Environments

Wonsick

Long²,

Onol

et al. 2021

Front. Robot. AI

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Nuclear energy will play a critical role in meeting clean energy targets worldwide. However, nuclear environments are dangerous for humans to operate in due to the presence of highly radioactive materials. Robots can help address this issue by allowing remote access to nuclear and other highly hazardous facilities under human supervision to perform inspection and maintenance tasks during normal operations, help with clean-up missions, and aid in decommissioning. This paper presents our research to help realize humanoid robots in supervisory roles in nuclear environments. Our research focuses on National Aeronautics and Space Administration (NASA’s) humanoid robot, Valkyrie, in the areas of constrained manipulation and motion planning, increasing stability using support contact, dynamic non-prehensile manipulation, locomotion on deformable terrains, and human-in-the-loop control interfaces.

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“…Coordinating multiple robotic arms for object manipulation has been studied extensively in the robotics literature, one can find comprehensive surveys on dual/multi-arm motion planning in the literature (Caccavale and Uchiyama, 2016; Smith et al, 2012; Wimböck et al, 2012; Wimböck and Ott, 2012). However, the problem of planning the reach to grasp motion for a moving object with a multi-arm robotic system, while keeping coordination constraints, is a new field of research.…”

Section: Related Workmentioning

confidence: 99%

“…Due to the technological difficulties that entail coordinating multiple arms with a dynamic object in a computationally efficient way, these applications have yet to be explored in the robotics community. Most effort in the field of multi-arm control has focused primarily on devising strategies for coordinated manipulation of static objects that are partially or fully grasped by the multi-arm system (Caccavale and Uchiyama, 2016). Seldom work has focused on developing coordinated strategies that a multi-arm system can use to reach and grab moving objects synchronously , while also being capable of reaching for independent targets or objects asynchronously (Vahrenkamp et al, 2012, 2010).…”

Section: Introductionmentioning

confidence: 99%

A unified framework for coordinated multi-arm motion planning

Salehian

Figueroa

Billard

2018

The International Journal of Robotics Research

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Coordination is essential in the design of dynamic control strategies for multi-arm robotic systems. Given the complexity of the task and dexterity of the system, coordination constraints can emerge from different levels of planning and control. Primarily, one must consider task-space coordination, where the robots must coordinate with each other, with an object or with a target of interest. Coordination is also necessary in joint space, as the robots should avoid self-collisions at any time. We provide such joint-space coordination by introducing a centralized inverse kinematics (IK) solver under self-collision avoidance constraints, formulated as a quadratic program and solved in real-time. The space of free motion is modeled through a sparse non-linear kernel classification method in a data-driven learning approach. Moreover, we provide multi-arm task-space coordination for both synchronous or asynchronous behaviors. We define a synchronous behavior as that in which the robot arms must coordinate with each other and with a moving object such that they reach for it in synchrony. In contrast, an asynchronous behavior allows for each robot to perform independent point-to-point reaching motions. To transition smoothly from asynchronous to synchronous behaviors and vice versa, we introduce the notion of synchronization allocation. We show how this allocation can be controlled through an external variable, such as the location of the object to be manipulated. Both behaviors and their synchronization allocation are encoded in a single dynamical system. We validate our framework on a dual-arm robotic system and demonstrate that the robots can re-synchronize and adapt the motion of each arm while avoiding self-collision within milliseconds. The speed of control is exploited to intercept fast moving objects whose motion cannot be predicted accurately.

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Cooperative Manipulation

Cited by 38 publications

References 54 publications

Dexterous Manipulation

Dexterous Manipulation

A Holistic Approach to Human-Supervised Humanoid Robot Operations in Extreme Environments

A unified framework for coordinated multi-arm motion planning

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