A path planning and path-following control framework for a general 2-trailer with a car-like tractor

Maneuvering a general 2-trailer with a car-like tractor in backward motion is a task that requires significant skill to master and is unarguably one of the most complicated tasks a truck driver has to perform. This paper presents a path planning and path-following control solution that can be used to automatically plan and execute difficult parking and obstacle avoidance maneuvers by combining backward and forward motion. A lattice-based path planning framework is developed in order to generate kinematically feasible and collision-free paths and a path-following controller is designed to stabilize the lateral and angular path-following error states during path execution. To estimate the vehicle state needed for control, a nonlinear observer is developed which only utilizes information from sensors that are mounted on the car-like tractor, making the system independent of additional trailer sensors. The proposed path planning and path-following control framework is implemented on a full-scale test vehicle and results from simulations and real-world experiments are presented.Comment: Preprin

The rolling problem: overview and challenges

In the present paper we give a historical account -ranging from classical to modern results- of the problem of rolling two Riemannian manifolds one on the other, with the restrictions that they cannot instantaneously slip or spin one with respect to the other. On the way we show how this problem has profited from the development of intrinsic Riemannian geometry, from geometric control theory and sub-Riemannian geometry. We also mention how other areas -such as robotics and interpolation theory- have employed the rolling model.Comment: 20 page

Efficient mobile robot path planning by Voronoi-based heuristic

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A Geometric Approach to Trajectory Planning for Underactuated Mechanical Systems

In the last decade, multi-rotors flying robots had a rapid development in industry and hobbyist communities thanks to the affordable cost and their availability of parts and components. The high number of degrees of freedom and the challenging dynamics of multi-rotors gave rise to new research problems. In particular, we are interested in the development of technologies for an autonomous fly that would al- low using multi-rotors systems to be used in contexts where the presence of humans is denied, for example in post-disaster areas or during search-and-rescue operations. Multi-rotors are an example of a larger category of robots, called \u201cunder-actuated mechanical systems\u201d (UMS) where the number of actuated degrees of freedom (DoF) is less than the number of available DoF. This thesis applies methods com- ing from geometric mechanics to study the under-actuation problem and proposes a novel method, based on the Hamiltonian formalism, to plan a feasible trajectory for UMS. We first show the application of a method called \u201cVariational Constrained System approach\u201d to a cart-pole example. We discovered that it is not possible to extend this method to generic UMS because it is valid only for a sub-class of UMS, called \u201csuper-articulated\u201d mechanical system. To overcome this limitation, we wrote the Hamilton equations of the quad- rotor and we apply a numerical \u201cdi- rect method\u201d to compute a feasible trajectory that satisfies system and endpoint constraints. We found that by including the system energy in the multi-rotor states, we are able to compute maneuvers that cannot be planned with other methods and that overcome the under-actuation constraints. To demonstrate the benefit of the method developed, we built a custom quad- rotor and an experimental setup with different obstacles, such as a gap in a wall and we show the correctness of the trajectory computed with the new method

Kinematic Modeling And Path Planning With Collision Avoidance For Multiple Cartesian Arms

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2006Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2006Kartezyen robotlar, endüstride geniş kullanım alanı bulmaktadır. Birden fazla kartezyen robotun ortak bir iş yapmasına gerek duyulan durumlar vardır. Bu tezde yapılan çalışmanın temeli, aynı çalışma uzayındaki kartezyen robotların çarpışma olmaksızın yörünge planlamasıdır. Bu çalışmanın amacı, aynı çalışma uzayındaki kartezyen robotların konumlandırılması için gerekli algoritmaları bulmak veya türetmektir. Çarpışma sakınımlı yörünge planlaması algoritmalarını kullanarak istenen işin başarılması uzaysal işlem cebriyle kinematik olarak modellenmiş robotik sisteme dayanır. Yörünge planlaması metodları kartezyen robotlara uygulanarak çarpışma olmayan yörüngenin bulunması için algoritmalar geliştirilir.Cartesian robots are already being widely used in industry and their use will substantially increase as the developing technology brings the prices down of high payload and high precision linear motors. There are applications where more than one cartesian robots are required to perform a common task. The focus of the research presented in this thesis is the collision free path planning for multiple cartesian robots sharing the same task space. The objective of this research is to obtain or derive necessary algorithms to coordinate multiple cartesian robots sharing the same workspace. Using path planning algorithms with collision avoidance, the desired task is achieved based on the kinematic model of the complete robotic system which is rooted in the spatial operator algebra. Path planning methods are applied to the cartesian robots and the algorithms to find collision-free path for the cartesian robots are developed.Yüksek LisansM.Sc

Sliding mode control applied in trajectory-tracking of WMRs and autonomous vehicles

Tese de doutoramento apresentada à Fac. de Ciências e Tecnologia da Universidade de CoimbraThe thesis is structured as follows: • Chapter 2: Trajectory tracking problems are summarized. • Chapter 3: Kinematic and dynamic modeling of theWMRs and car-like robots are presented. • Chapter 4: The concept of sliding mode are first introduced. Then the fundamentals of SMC are summarized, including basic definitions, methods of sliding surface and control law design, robustness properties and the methods on handling chattering problems. New sliding-mode trajectory-tracking and slidingmode path-following controllers for WMRs and car-like vehicles, are also proposed in this chapter. • Chapter 5: The trajectory/path planning are developed, including the velocity profile. • Chapter 6: A model with two freedom degrees is considered for the HNC model. The user comfort is examined not only in the time domain, but also in the frequency domain. • Chapter 7: Experimental results obtained with the implementation of the proposed controllers in RobChair are summarized and discussed. • Chapter 8: Finally, conclusions are drawn and some suggestions for future work are provided

Perception Based Navigation for Underactuated Robots.

Robot autonomous navigation is a very active field of robotics. In this thesis we propose a hierarchical approach to a class of underactuated robots by composing a collection of local controllers with well understood domains of attraction. We start by addressing the problem of robot navigation with nonholonomic motion constraints and perceptual cues arising from onboard visual servoing in partially engineered environments. We propose a general hybrid procedure that adapts to the constrained motion setting the standard feedback controller arising from a navigation function in the fully actuated case. This is accomplished by switching back and forth between moving "down" and "across" the associated gradient field toward the stable manifold it induces in the constrained dynamics. Guaranteed to avoid obstacles in all cases, we provide conditions under which the new procedure brings initial configurations to within an arbitrarily small neighborhood of the goal. We summarize with simulation results on a sample of visual servoing problems with a few different perceptual models. We document the empirical effectiveness of the proposed algorithm by reporting the results of its application to outdoor autonomous visual registration experiments with the robot RHex guided by engineered beacons. Next we explore the possibility of adapting the resulting first order hybrid feedback controller to its dynamical counterpart by introducing tunable damping terms in the control law. Just as gradient controllers for standard quasi-static mechanical systems give rise to generalized "PD-style" controllers for dynamical versions of those standard systems, we show that it is possible to construct similar "lifts" in the presence of non-holonomic constraints notwithstanding the necessary absence of point attractors. Simulation results corroborate the proposed lift. Finally we present an implementation of a fully autonomous navigation application for a legged robot. The robot adapts its leg trajectory parameters by recourse to a discrete gradient descent algorithm, while managing its experiments and outcome measurements autonomously via the navigation visual servoing algorithms proposed in this thesis.Ph.D.Electrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58412/1/glopes_1.pd

Energetic swarm control with application to multiple vehicle systems

Control and coordination of multiple vehicle systems has been a very active area of research in recent years. Recent advancements in computation, communication, and mechatronics have allowed the development of large groups of vehicles, often referred to as swarms, in order to accomplish complex missions over large areas with redundant fault tolerant capabilities. Existing swarm control work has addressed swarm aggregation, foraging swarms, swarm formation, and swarms that track and enclose targets. Energetic swarm control is another significant recent contribution to the swarm control literature. It allows the control of the internal kinetic energy and potential kinetic energy of the swarm system in order to achieve tasks such as sweeping an area, patrolling, and area coverage. This thesis involves the application of energetic swarm control to wheeled mobile robots. A lower level control layer for wheeled mobile robots, based on feedback linearization, is developed and combined with a higher level particle based energetic swarm controller. Furthermore, input saturation constraints are addressed using a suitable control allocation approach. An experimentally verified model of a wheeled mobile robot is developed and used to demonstrate the capabilities of the new energetic swarm control approach for wheeled mobile robots

Full 3D motion control for programmable bevel-tip steerable needles

Minimally invasive surgery has been in the focus of many researchers due to its reduced intra- and post-operative risks when compared to an equivalent open surgery approach. In the context of minimally invasive surgery, percutaneous intervention, and particularly, needle insertions, are of great importance in tumour-related therapy and diagnosis. However, needle and tissue deformation occurring during needle insertion often results in misplacement of the needles, which leads to complications, such as unsuccessful treatment and misdiagnosis. To this end, steerable needles have been proposed to compensate for placement errors by allowing curvilinear navigation. A particular type of steerable needle is the programmable bevel-tip steerable needle (PBN), which is a bio-inspired needle that consists of relatively soft and slender segments. Due to its flexibility and bevel-tip segments, it can navigate through 3D curvilinear paths. In PBNs, steering in a desired direction is performed by actuating particular PBN segments. Therefore, the pose of each segment is needed to ensure that the correct segment is actuated. To this end, in this thesis, proprioceptive sensing methods for PBNs were investigated. Two novel methods, an electromagnetic (EM)-based tip pose estimation method and a fibre Bragg grating (FBG)-based full shape sensing method, were presented and evaluated. The error in position was observed to be less than 1.08 mm and 5.76 mm, with the proposed EM-based tip tracking and FBG-based shape reconstruction methods, respectively. Moreover, autonomous path-following controllers for PBNs were also investigated. A closed-loop, 3D path-following controller, which was closed via feedback from FBG-inscribed multi-core fibres embedded within the needle, was presented. The nonlinear guidance law, which is a well-known approach for path-following control of aerial vehicles, and active disturbance rejection control (ADRC), which is known for its robustness within hard-to-model environments, were chosen as the control methods. Both linear and nonlinear ADRC were investigated, and the approaches were validated in both ex vivo brain and phantom tissue, with some of the experiments involving moving targets. The tracking error in position was observed to be less than 6.56 mm.Open Acces