Concentric tube continuum robots (CTCRs) belong to the family of continuum robots with applications in minimally invasive surgeries. Because of this application domain, measuring the external forces along the body of ...
Concentric tube continuum robots (CTCRs) belong to the family of continuum robots with applications in minimally invasive surgeries. Because of this application domain, measuring the external forces along the body of the robot is paramount. CTCRs are made up of thin elastic rods and are intended to be applied inside the human body, where conventional sensor-based measurements are not feasible. Consequently, research is resorting to estimate the forces through geometric, numeric, or optimization methods. However, these methods often suffer from slow convergence. In this paper, we introduce a novel data-driven approach for estimating contact forces along the body of a CTCR that offers an estimation precision comparable to the current state-of-the-art optimization-based approaches, but exhibits nearly two orders of magnitude faster convergence. The proposed method is scalable and exhibits a significant performance in response to a wide range of external forces. The approach was evaluated in simulations and on a real 2-tube CTCR.
The kinematic structure of Franka Emika's redundant cobot Panda features two translational offsets that prevent three of the six pairs of adjacent joints from intersecting each other. These offsets make Panda'...
The kinematic structure of Franka Emika's redundant cobot Panda features two translational offsets that prevent three of the six pairs of adjacent joints from intersecting each other. These offsets make Panda's elbow motion in null space hard to predict with respect to existing redundancy parameters. The null space motion analysis of Panda's elbow presented in this work leads to the definition of a redundancy parameter that can be used intuitively. The semi-analytical approach applied in this work induces a fast inverse kinematics algorithm that offers a redundancy resolution which does not affect the reachability of the given end effector pose. Even libfranka, Franka Emika's supplied library, does not offer such a Cartesian approach of keeping control of Panda's secondary motion while fulfilling primary manipulation tasks.
The redundant light-weight robot Franka Emika Panda is omnipresent in modern research like human-robot interaction or machine learning. Much of that research requires to solve the inverse kinematics problem (IKP) prop...
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ISBN:
(纸本)9781665436854
The redundant light-weight robot Franka Emika Panda is omnipresent in modern research like human-robot interaction or machine learning. Much of that research requires to solve the inverse kinematics problem (IKP) properly. This paper presents an analytical solution for the IKP based on the geometry of the manipulator's kinematic structure. It also provides information on how the redundancy is resolved and how singularities are handled. The whole procedure is a concatenation of intersection and closest point problems of two or three dimensional objects, for which at least basic solutions already exist. Consequently, the approach is lightweight in calculation and, in addition, very robust when it comes to finding solutions for rare edge cases. On the top of that, the simple nature of calculations make the approach utilizable in a real-time safe fashion. Hence, an implementation in C++ is given as open source library, which also can be used to validate the results of this paper.
Incremental Manufacturing is a novel approach for the production of functional multi-material components with a large number of variants per part. It combines established production processes with additive and subtrac...
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Incremental Manufacturing is a novel approach for the production of functional multi-material components with a large number of variants per part. It combines established production processes with additive and subtractive manufacturing technologies. The idea of Incremental Manufacturing comprises the robot-based and thus geometry-flexible step-by-step additive finalisation of prefabricated basic parts (semi-finished products, e.g. sheets, profiles) with a high build-up rate and, if needed, subsequent subtractive finishing of functional surfaces. This concept offers new ways for efficient and volume-capable variant production by reducing variant-specific investments. However, the elevated degree of freedom raises new challenges in the domains of product, process-, control- and software-design, since the classic straightforward production planning from product to process proves infeasible to manage the arising flexibility and configurability of Incremental Manufacturing. To cope with these new challenges, this paper introduces an approach to use AutomationML for the modelling of the degree of freedom in product, process and in the hardware set-up design through a hardware-neutral description of the manufacturing process. The aim is to develop a specific process description using the example of additive manufacturing, which can be used for reconfigurable hardware set-ups and a flexible production design. Therefore, the authors present an AutomationML-based architecture for process modelling and constraint management based on manufacturing process knowledge to ensure a highly flexible Incremental Manufacturing.
We consider a virtual manipulator in grasping scenarios which allows us to capture the effect of the object dynamics. This modeling approach turns a multi-arm robot into an underactuated system. We observe that contro...
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We consider a virtual manipulator in grasping scenarios which allows us to capture the effect of the object dynamics. This modeling approach turns a multi-arm robot into an underactuated system. We observe that controlling floating-base multi-leg robots is fundamentally similar. The Projected Inverse Dynamics control approach is employed for decoupling contact consistent motion generation and controlling contact wrenches. The proposed framework for underactuated robots has been evaluated on an enormous robot hand composed of four KUKA LWR IV+ representing fingers cooperatively manipulating a 9kg box with total 28 actuated DOF and six virtual DOF representing the object as additional free-floating robot link. Finally, we validate the same approach on ANYmal, a floating-base quadruped with 12 actuated DOF. Experiments are performed both in simulation and real world.
In this paper, the problem of trajectory optimization for the Compliant huMANoid robot (COMAN) arm is solved by Dynamic Programming. It is based on dimensionality reduction and uses a path parameter to convert the dyn...
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ISBN:
(纸本)9781509047192
In this paper, the problem of trajectory optimization for the Compliant huMANoid robot (COMAN) arm is solved by Dynamic Programming. It is based on dimensionality reduction and uses a path parameter to convert the dynamical equations of the robotic manipulator to a set of second order differential equations. First, the path parameter is calculated from the given geometrical path information and then the path parameter based reduced dynamical equations and the terminal conditions are described in the discretized form. Bellman's optimality principle is applied to calculate the minimum performance index and to optimize the objective function. To show the effectiveness of path parameter based Dynamic Programming approach, it is tested on a simulation of the COMAN robot arm and the obtained optimal results are compared in terms of numerical accuracy and computational time with the optimal solutions obtained by other state-of-the-art techniques.
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