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Articulated robot

About: Articulated robot is a research topic. Over the lifetime, 4364 publications have been published within this topic receiving 52442 citations.


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Proceedings ArticleDOI
09 May 2011
TL;DR: A new pipeline inspection robot that has multiple sensors for inspection of 80–100mm pipelines by using only two wheel chains, which allows simple robot control and easy user interface, specially at T-branch.
Abstract: This paper presents a new pipeline inspection robot that has multiple sensors for inspection of 80–100mm pipelines. The special feature of this robot is realization of driving and steering capability by using only two wheel chains. Compared to popularly employed pipeline robots using three wheel chains, the new design allows simple robot control and easy user interface, specially at T-branch. As another advantage, the flat shape of this robot allows mounting additional sensors on the both sides of the robot. The kinematics and three control modes are described. Finally, the performance of this robot system is verified by experimentation.

40 citations

Proceedings ArticleDOI
20 Oct 2014
TL;DR: This paper addresses the problem of teaching a robot collaborative behaviors from human demonstrations by presenting an approach that combines: probabilistic learning and dynamical systems, to encode the robot's motion along the task.
Abstract: Physical interaction between humans and robots arises a large set of challenging problems involving hardware, safety, control and cognitive aspects, among others. In this context, the cooperative (two or more people/robots) transportation of bulky loads in manufacturing plants is a practical example where these challenges are evident. In this paper, we address the problem of teaching a robot collaborative behaviors from human demonstrations. Specifically, we present an approach that combines: probabilistic learning and dynamical systems, to encode the robot's motion along the task. Our method allows us to learn not only a desired path to take the object through, but also, the force the robot needs to apply to the load during the interaction. Moreover, the robot is able to learn and reproduce the task with varying initial and final locations of the object. The proposed approach can be used in scenarios where not only the path to be followed by the transported object matters, but also the force applied to it. Tests were successfully carried out in a scenario where a 7 DOFs backdrivable manipulator learns to cooperate, with a human, to transport an object while satisfying the position and force constraints of the task.

40 citations

Proceedings ArticleDOI
13 Oct 1998
TL;DR: A new lightweight six-legged robot is developed which uses a simple mechanism and can move and work with high efficiency and has satisfactory performance not only as a walking robot but also as an active walking platform.
Abstract: A new lightweight six-legged robot is developed which uses a simple mechanism and can move and work with high efficiency. This robot consists of two leg-bases with three legs each and walks by moving each leg-base alternately. These leg-bases are connected to each other through a 6-DOF mechanism. Thus, when the robot stands on three legs, or one leg-base is placed on the ground, the other leg-base can be used as a 6-DOF manipulator or active working platform. The output force, velocity, and movable range of various mechanisms for connecting the two leg-bases were compared and the results showed that good performance could be achieved with a serial-parallel hybrid mechanism consisting of three 6-DOF serial linked arms positioned with radial symmetry about the center of each leg-base, each composed of two active and four passive joints. Walking experiments with this robot confirm that this mechanism has satisfactory performance not only as a walking robot but also as an active walking platform.

39 citations

Proceedings ArticleDOI
10 Dec 2007
TL;DR: A case study of cooperation of a strongly heterogeneous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some competing capabilities, is presented.
Abstract: In this paper we present a case study of cooperation of a strongly heterogeneous robot team, composed of a highly articulated humanoid robot and a wheeled robot with largely complementing and some competing capabilities. By combining two strongly heterogeneous robots the diversity of accomplishable tasks increases as the variety of sensors and actuators in the robot systems is extended compared with a team consisting of homogeneous robots. The scenario describes a tightly cooperative task, where the humanoid robot and the wheeled robot follow for a long distance a ball, which is kicked finally by the humanoid robot into a goal. The task can be fulfilled successfully by combining the abilities of both robots. For task distribution and allocation, a newly developed objective function is presented which is based on a proper modeling of the sensing, perception, motion and onboard computing capabilities of the cooperating robots. Aspects of reliability and fault tolerance are considered.

39 citations

Proceedings ArticleDOI
26 May 2015
TL;DR: This work presents a motion planning approach for concentric tube robot teleoperation that enables the robot to interactively maneuver its tip to points selected by a user while automatically avoiding obstacles along its shaft.
Abstract: Concentric tube robots are thin, tentacle-like devices that can move along curved paths and can potentially enable new, less invasive surgical procedures. Safe and effective operation of this type of robot requires that the robot's shaft avoid sensitive anatomical structures (e.g., critical vessels and organs) while the surgeon teleoperates the robot's tip. However, the robot's unintuitive kinematics makes it difficult for a human user to manually ensure obstacle avoidance along the entire tentacle-like shape of the robot's shaft. We present a motion planning approach for concentric tube robot teleoperation that enables the robot to interactively maneuver its tip to points selected by a user while automatically avoiding obstacles along its shaft. We achieve automatic collision avoidance by precomputing a roadmap of collision-free robot configurations based on a description of the anatomical obstacles, which are attainable via volumetric medical imaging. We also mitigate the effects of kinematic modeling error in reaching the goal positions by adjusting motions based on robot tip position sensing. We evaluate our motion planner on a teleoperated concentric tube robot and demonstrate its obstacle avoidance and accuracy in environments with tubular obstacles.

39 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20233
20227
202152
202060
201965
201877