Analytical Inverse Kinematic Computation for 7-DOF Redundant Manipulators With Joint Limits and Its Application to Redundancy Resolution

Shimizu, Masayuki; Kakuya, Hiromu; Yoon, Woo-Keun; Kitagaki, K.; Kosuge, Kazuhiro

doi:10.1109/tro.2008.2003266

Cited by 269 publications

(133 citation statements)

References 14 publications

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“…It is shown in ref. [26] that similar approach works well for a redundant manipulator with a wrist. But, this issue has not been addressed yet, and further research will be required.…”

Section: Extension and Limitation Of Inverse Kinematic Solving Methodsmentioning

confidence: 75%

Analytical inverse kinematics for 5-DOF humanoid manipulator under arbitrarily specified unconstrained orientation of end-effector

Shimizu

2014

Robotica

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SUMMARYThis paper proposes an analytical method of solving the inverse kinematic problem for a humanoid manipulator with five degrees-of-freedom (DOF) under the condition that the target orientation of the manipulator's end-effector is not constrained around an axis fixed with respect to the environment. Since the number of the joints is less than six, the inverse kinematic problem cannot be solved for arbitrarily specified position and orientation of the end-effector. To cope with the problem, a generalized unconstrained orientation is introduced in this paper. In addition, this paper conducts the singularity analysis to identify all singular conditions.

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“…It is shown in ref. [26] that similar approach works well for a redundant manipulator with a wrist. But, this issue has not been addressed yet, and further research will be required.…”

Section: Extension and Limitation Of Inverse Kinematic Solving Methodsmentioning

confidence: 75%

Analytical inverse kinematics for 5-DOF humanoid manipulator under arbitrarily specified unconstrained orientation of end-effector

Shimizu

2014

Robotica

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“…The inverse kinematic function used the algorithm of Shimizu et al (2008). The redundancy of the robot arm was not employed, and the corresponding redundancy parameters were kept constant at appropriate values.…”

Section: Robot Controlmentioning

confidence: 99%

A Neural Network-Based Approach for Trajectory Planning in Robot–Human Handover Tasks

et al. 2016

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Service robots and even industrial robots recently started sharing human workspace for creating new working settings where humans and robots work even hand by hand. On the one hand, this new scenario raises problems of safety, which are being solved by adding suitable sensor batteries to robot control systems, and on the other hand, it entails dealing with psychophysical aspects as well. Motion intention understanding and prediction comes more natural and effective if the controlled movement is biologically inspired. In order to generate biologically inspired movements in a robotic-assisted surgery scenario, where a robotic assistant shares the execution of tasks with, or hands over tools to a surgeon, we designed a trajectory planning system based on an artificial neural network architecture trained on human actions. After the design and training of the neural controller for motion planning, we checked the objective characteristics of the achieved biologically inspired motion as functional minimization (minimum jerk), two-third power law and bell-shaped velocity. The controller was also experimentally implemented by using a redundant serial robotic arm (LWR4+, Kuka, Germany), and it was actually perceived as "human-like" in the majority of cases by naive subjects. The implemented neural-based control strategy provided to be an effective scheme for human-robot interaction control, also by qualitative assessment.

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“…Continuity constraints due to the physical joint limits [10] were taken into account in the NSO strategy, because they cause discontinuities in the available ns values, thus possibly leading to unacceptable regions within the predefined ROM. The set of feasible null space values Ψ k that satisfies the k-th joint limit is described as:…”

Section: Physical Joint Limits Managementmentioning

confidence: 99%

Redundancy optimization strategy for hands-on robotic surgery

Barra

Beretta

Nessi

et al. 2015

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Abstract-During hands-on cooperative surgery, the use of a redundant robot allows to address encumbrance issues in the Operating Room (OR), which can occur due to the presence of large medical instrumentation, such as the surgical microscope. This work presents a new Null Space Optimization (NSO) strategy to constraint the position of the manipulator's elbow within predefined range of motions, according to the spatial requirements of the specific procedure, also taking into account the physical joint limits of the robotic assistant. The proposed strategy was applied to the 7 degrees of freedom (dof) lightweight robot LWR4+. The performance of the NSO was compared to two state-of-the-art null space optimization strategies, i.e. damped posture and fixed optimal posture, over a pool of three non-expert users in both strict (20deg) and negligible (100deg) angular encumbrance limitations. The NSO strategy was proved versatile in providing wide elbow mobility together with safe distance from relevant continuity null space boundaries, guaranteeing smooth guidance trajectories. Future works would be performed in order to evaluate the potential feasibility of NSO in a real surgical scenario.

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Analytical Inverse Kinematic Computation for 7-DOF Redundant Manipulators With Joint Limits and Its Application to Redundancy Resolution

Cited by 269 publications

References 14 publications

Analytical inverse kinematics for 5-DOF humanoid manipulator under arbitrarily specified unconstrained orientation of end-effector

Analytical inverse kinematics for 5-DOF humanoid manipulator under arbitrarily specified unconstrained orientation of end-effector

A Neural Network-Based Approach for Trajectory Planning in Robot–Human Handover Tasks

Redundancy optimization strategy for hands-on robotic surgery

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