On-line Optimization of Avoidance Ability for Redundant Manipulator

Ikeda, Keiji; Tanaka, Hiroshi; Zhang, Tongxiao; Minami, Mamoru; Mae, Yasushi

doi:10.1109/iros.2006.282537

Cited by 20 publications

(13 citation statements)

References 6 publications

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“…In reference [9], the concept of avoidance ability was used to the motion plan of a redundant manipulator, firstly the avoidance manipulability ellipsoid is defined. The volume of i-th link's avoidance manipulability ellipsoid 1 V i is given as:…”

Section: Manipulability Analysismentioning

confidence: 99%

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Trajectory planning for a redundant mobile manipulator using avoidance manipulability

Cui

Cao

Shao

et al. 2009

2009 IEEE International Conference on Automation and Logistics

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A Trajectory planning method for a mobile manipulator is proposed in this paper. The mobile manipulator studied here consists of a mobile platform and a redundant manipulator. Since the system has the redundant degree of freedom to perform some tasks, it will have infinite configurations to make the end-effector track the desired trajectory. The concept of AMSI and AMSIP which were used to optimize the avoidance ability for redundant manipulator is extended to carry out the trajectory planning in this paper. We firstly predefine the trajectory of the mobile platform and stop it at a certain position defined by AMSI where allows the manipulator to reach all the desired points on the trajectory, then optimize the configuration of the manipulator according to AMSI and AMSIP to realize the whole trajectory planning task. The experiments are performed by the mobile manipulator in real environment.

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Section: Manipulability Analysismentioning

confidence: 99%

“…The detailed implementation can be referred to reference [9], the concept of AMSI and AMSIP was used to plan the motion of a redundant manipulator, in this paper, we will extend AMSI and AMSIP to the trajectory planning of a mobile manipulator and demonstrate how to realize the planning in the following sections.…”

Section: Manipulability Analysismentioning

confidence: 99%

Trajectory planning for a redundant mobile manipulator using avoidance manipulability

Cui

Cao

Shao

et al. 2009

2009 IEEE International Conference on Automation and Logistics

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“…Therefore, 1 S will come down by U and the possibility of the collision will increase once the manipulator moves into potential spaces (detail explanation of potential spaces is shown in [7]). (b) Manipulator's optimal configuration based on AMSIP Fig.…”

Section: B Amsipmentioning

confidence: 99%

“…Therefore, in the whole on-line trajectory tracking process, always keeping the avoidance manipulability (see [5]) of whole manipulator high is very important. Based on this requirement of high avoidance manipulability, to optimize trajectory tracking and obstacle avoidance online, we adopt 1-step Genetic Algorithm (see [6]) considering potential spaces (see [7]) around the measured target object, to search real-time optimal configurations of the manipulator at future times. Then, we present multi-preview control for solving reachability problem according to the concept of preview control (see [8]).…”

Section: Introductionmentioning

confidence: 99%

Multi-preview configuration control for redundant manipulator by future reachability evaluation

Zhang

Minami

Song

2007

2007 IEEE/RSJ International Conference on Intelligent Robots and Systems

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This paper proposes a new approach to achieve an on-line control of trajectory tracking and obstacle avoidance for redundant manipulators without prechecking path-planning in whole trajectory tracking. In the trajectory tarcking process, manipulator is required to keep a configuration with maximal avoidance manipulability in real-time. In this paper, we present a new idea: Multi-Preview Control, which uses several future optimal configurations to control current configuration to complete task of trajectory tracking and obstacle avoidance online with high avoidance manipulability and reachability. We verify the validity of multi-preview control through simulations of comparing single-preview control with multi-preview control.

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“…However, the eye-in-hand sensor has limitations in reporting collisions or -space mapping capability in realtime due to visual occlusion. Other studies on sensor based planning of manipulators include [13], where an avoidance ability for redundant manipulators is studied with a moving camera on the ceiling. Trajectory planning for a redundant mobile manipulator is studied using avoidance manipulability concept [14].…”

Section: Introductionmentioning

confidence: 99%

SPAM for a Manipulator by Best Next Move in Unknown Environments

Ryu

2013

ISRN Robotics

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We propose a SPAM (simultaneous planning and mapping) technique for a manipulator-type robot working in an uncertain environment via a novel Best Next Move algorithm. Demands for a smart decision to move a manipulator such as humanoid arms in uncertain or crowded environments call for a simultaneous planning and mapping technique. In the present work, we focus more on rapid map generation rather than global path search to reduce ignorance level of a given environment. The motivation is that the global path quality will be improved as the ignorance level of the unknown environment decreases. The 3D sensor introduced in the previous work has been improved for better mapping capability and the real-time rehearsal idea is used for -space cloud point generation. Captured cloud points by 3D sensors, then, create an instantaneous -space map whereby the Best Next Move algorithm directs the local motion of the manipulator. The direction of the Best Next Move utilizes the gradient of the density distribution of the -nearest-neighborhood sets in -space. It has a tendency of traveling along the direction by which the point clouds spread in space, thus rendering faster mapping of -space obstacles possible. The proposed algorithm is compared with a sensor-based algorithm such as sensor-based RRT for performance comparison. Performance measures, such as mapping efficiency, search time, and total number of -space point clouds, are reported as well. Possible applications include semiautonomous telerobotics planning and humanoid arm path planning.

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On-line Optimization of Avoidance Ability for Redundant Manipulator

Cited by 20 publications

References 6 publications

Trajectory planning for a redundant mobile manipulator using avoidance manipulability

Trajectory planning for a redundant mobile manipulator using avoidance manipulability

Multi-preview configuration control for redundant manipulator by future reachability evaluation

SPAM for a Manipulator by Best Next Move in Unknown Environments

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