1,537 research outputs found
A modal approach to hyper-redundant manipulator kinematics
This paper presents novel and efficient kinematic modeling techniques for “hyper-redundant” robots. This approach is based on a “backbone curve” that captures the robot's macroscopic geometric features. The inverse kinematic, or “hyper-redundancy resolution,” problem reduces to determining the time varying backbone curve behavior. To efficiently solve the inverse kinematics problem, the authors introduce a “modal” approach, in which a set of intrinsic backbone curve shape functions are restricted to a modal form. The singularities of the modal approach, modal non-degeneracy conditions, and modal switching are considered. For discretely segmented morphologies, the authors introduce “fitting” algorithms that determine the actuator displacements that cause the discrete manipulator to adhere to the backbone curve. These techniques are demonstrated with planar and spatial mechanism examples. They have also been implemented on a 30 degree-of-freedom robot prototype
Safety-related Tasks within the Set-Based Task-Priority Inverse Kinematics Framework
In this paper we present a framework that allows the motion control of a
robotic arm automatically handling different kinds of safety-related tasks. The
developed controller is based on a Task-Priority Inverse Kinematics algorithm
that allows the manipulator's motion while respecting constraints defined
either in the joint or in the operational space in the form of equality-based
or set-based tasks. This gives the possibility to define, among the others,
tasks as joint-limits, obstacle avoidance or limiting the workspace in the
operational space. Additionally, an algorithm for the real-time computation of
the minimum distance between the manipulator and other objects in the
environment using depth measurements has been implemented, effectively allowing
obstacle avoidance tasks. Experiments with a Jaco manipulator, operating in
an environment where an RGB-D sensor is used for the obstacles detection, show
the effectiveness of the developed system
Non-singular assembly mode changing trajectories in the workspace for the 3-RPS parallel robot
Having non-singular assembly modes changing trajectories for the 3-RPS
parallel robot is a well-known feature. The only known solution for defining
such trajectory is to encircle a cusp point in the joint space. In this paper,
the aspects and the characteristic surfaces are computed for each operation
mode to define the uniqueness of the domains. Thus, we can easily see in the
workspace that at least three assembly modes can be reached for each operation
mode. To validate this property, the mathematical analysis of the determinant
of the Jacobian is done. The image of these trajectories in the joint space is
depicted with the curves associated with the cusp points
A technique based on adaptive extended jacobians for improving the robustness of the inverse numerical kinematics of redundant robots
The extended Jacobian is a technique for solving the redundancy of redundant robots. It is based on the definition of secondary tasks, through constraint functions that are added to the mapping between joint rates and end-effector's twist. Several approaches showed its potential, applications, and limitations. In general, the constraint functions are a linear combination of basic functions with constant coefficients. This paper proposes the use of adaptive coefficients in such functions by using the conditioning index of the extended Jacobian as a quality measure. A good conditioning index of the extended Jacobian keeps the robot far from singularities and contributes to the solution of the inverse kinematics. In this paper, initially, the extended Jacobian and the proposed algorithm are discussed, and then, two tests in different circumstances are presented in order to validate the proposal
Pose consensus based on dual quaternion algebra with application to decentralized formation control of mobile manipulators
This paper presents a solution based on dual quaternion algebra to the
general problem of pose (i.e., position and orientation) consensus for systems
composed of multiple rigid-bodies. The dual quaternion algebra is used to model
the agents' poses and also in the distributed control laws, making the proposed
technique easily applicable to time-varying formation control of general
robotic systems. The proposed pose consensus protocol has guaranteed
convergence when the interaction among the agents is represented by directed
graphs with directed spanning trees, which is a more general result when
compared to the literature on formation control. In order to illustrate the
proposed pose consensus protocol and its extension to the problem of formation
control, we present a numerical simulation with a large number of free-flying
agents and also an application of cooperative manipulation by using real mobile
manipulators
Fast Manipulability Maximization Using Continuous-Time Trajectory Optimization
A significant challenge in manipulation motion planning is to ensure agility
in the face of unpredictable changes during task execution. This requires the
identification and possible modification of suitable joint-space trajectories,
since the joint velocities required to achieve a specific endeffector motion
vary with manipulator configuration. For a given manipulator configuration, the
joint space-to-task space velocity mapping is characterized by a quantity known
as the manipulability index. In contrast to previous control-based approaches,
we examine the maximization of manipulability during planning as a way of
achieving adaptable and safe joint space-to-task space motion mappings in
various scenarios. By representing the manipulator trajectory as a
continuous-time Gaussian process (GP), we are able to leverage recent advances
in trajectory optimization to maximize the manipulability index during
trajectory generation. Moreover, the sparsity of our chosen representation
reduces the typically large computational cost associated with maximizing
manipulability when additional constraints exist. Results from simulation
studies and experiments with a real manipulator demonstrate increases in
manipulability, while maintaining smooth trajectories with more dexterous (and
therefore more agile) arm configurations.Comment: In Proceedings of the IEEE International Conference on Intelligent
Robots and Systems (IROS'19), Macau, China, Nov. 4-8, 201
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