The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2

Friesen, Jeffrey M.; Glick, Paul; Fanton, Michael; Manovi, Pavlo; Xydes, Alexander; Bewley, Thomas; SunSpiral, Vytas

doi:10.1109/icra.2016.7487361

Cited by 30 publications

(16 citation statements)

References 11 publications

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“…The optimization problem of eqn. (27)(28)(29) is the standard form of tensegrity inverse kinematics as used in [20], [21]. If a feasible q is found, the rest lengths ρ i of each cable i ∈ {1, ..., s} are back-calculated from eqn.…”

Section: Force Density Methods For Tensegrity Networkmentioning

confidence: 99%

“…Such structures are inherently flexible, and many types of tensegrity robots have been designed that leverage this flexibility. These robots are able to adjust the lengths of their cables to roll [14], [15], crawl [16], [17], [18], swim [19], and climb [20], [21]. Tensegrity spine robots have been previously investigated [22], [18], but the ULTRA Spine and its recent adaptation for Laika are one of the first uses of a tensegrity spine on a quadruped robot [11], [8].…”

Section: A Tensegrity Robots and Controlmentioning

confidence: 99%

“…(24). In works such as [20], [11], [21], the tensegrity structure has many more cables and bars than nodes, such that (s + r) > (nd). Thus, A is wider than it is tall, with a null space dimension of at least (s + r) − (nd) > 0, so an infinite number of solutions exist to eqn.…”

Section: Existence Of Solutions and Rank Deficiencymentioning

confidence: 99%

See 2 more Smart Citations

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Sabelhaus

Zhao

Zhu

et al. 2021

IEEE Trans. Contr. Syst. Technol.

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Robots with flexible spines based on tensegrity structures have potential advantages over traditional designs with rigid torsos. However, these robots can be difficult to control due to their high-dimensional nonlinear dynamics. To overcome these issues, this work presents two controllers for tensegrity spine robots, using model-predictive control (MPC), and demonstrates the first closed-loop control of such structures. The first of the two controllers is formulated using only state tracking with smoothing constraints. The second controller, newly introduced in this work, tracks both state and input reference trajectories without smoothing. The reference input trajectory is calculated using a rigid-body reformulation of the inverse kinematics of tensegrity structures, and introduces the first feasible solutions to the problem for certain tensegrity topologies. This second controller significantly reduces the number of parameters involved in designing the control system, making the task much easier. The controllers are simulated with 2D and 3D models of a particular tensegrity spine, designed for use as the backbone of a quadruped robot. These simulations illustrate the different benefits of the higher performance of the smoothing controller versus the lower tuning complexity of the more general input-tracking formulation. Both controllers show noise insensitivity and low tracking error, and can be used for different control goals. The reference input tracking controller is also simulated against an additional model of a similar robot, thereby demonstrating its generality.

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Section: Force Density Methods For Tensegrity Networkmentioning

confidence: 99%

Section: A Tensegrity Robots and Controlmentioning

confidence: 99%

See 1 more Smart Citation

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Sabelhaus

Zhao

Zhu

et al. 2021

IEEE Trans. Contr. Syst. Technol.

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“…The unique arrangement of the members, where the compressive elements are not in contact between them, distributes the internal forces only along the axes of the elements thus removing the forces such as torque or bending from the design process. Thanks to their advantages of efficient force distribution, lightweight, and the possibility to apply control systems to some of its members, the use of tensegrity structures for soft robotics and smart structures has become an important research topic in recent years; some examples of these applications are the robotic icosahedrons (Bruce et al, 2014) (Ushigome et al, 2010) and snake-like crawling structures (Friesen et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration of multi-stage tensegrity structures using infinitesimal mechanisms

González

Luo

Shi

2019

Lat. Am. j. solids struct.

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The use of tensegrity structures in soft robotics has seen an increased interest in recent years thanks to their mechanical properties, but the control of these systems remains an open problem. This paper presents a reconfiguration strategy for actuated multi-stage tensegrity structures. The algorithm works on the principle of using the infinitesimal mechanisms of the structure to generate a path of positions along which a multistage tensegrity structure can change its shape while maintaining the self-equilibrium. Combining the force density method with a marching procedure, the solution to the equilibrium problem is given by a set of differential equations that define the kinematic constraints of the structure. Beginning from an initial stable position, the algorithm calculates a small displacement until a new stable configuration is reached, and recurrently repeats the process during a given interval of time. By means of three numerical examples, we show the efficacy of our algorithm for reconfiguring a two-stage tensegrity mast along different directions.

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“…For a novel tensegrity duct robot constructed with two linked tetrahedrons [9,10], the main focus is also on the design of climbing gaits. Through the structure design and kinematic analysis of a steering crawling tetrahedron robot which links a pushing element on one of its four nodes [11], the slope crawling gait was presented.…”

Section: Introductionmentioning

confidence: 99%

Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control

Liu

Yao

Ding

et al. 2018

Chin. J. Mech. Eng.

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Locomotion and manipulation optimization is essential for the performance of tetrahedron-based mobile mechanism. Most of current optimization methods are constrained to the continuous actuated system with limited degree of freedom (DOF), which is infeasible to the optimization of binary control multi-DOF system. A novel optimization method using for the locomotion and manipulation of an 18 DOFs tetrahedron-based mechanism called 5-TET is proposed. The optimization objective is to realize the required locomotion by executing the least number of struts. Binary control strategy is adopted, and forward kinematic and tipping dynamic analyses are performed, respectively. Based on a developed genetic algorithm (GA), the optimal number of alternative struts between two adjacent steps is obtained as 5. Finally, a potential manipulation function is proposed, and the energy consumption comparison between optimal 5-TET and the traditional wheeled robot is carried out. The presented locomotion optimization and manipulation planning enrich the research of tetrahedron-based mechanisms and provide the instruction to the successive locomotion and operation planning of multi-DOF mechanisms. Keywords

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The second generation prototype of a Duct Climbing Tensegrity robot, DuCTTv2

Cited by 30 publications

References 11 publications

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots

Reconfiguration of multi-stage tensegrity structures using infinitesimal mechanisms

Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control

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