Hybrid PSO-cubic spline for autonomous robots optimal trajectory planning

This paper presents a new version of the Particle Swarm Optimization algorithm where the particles are replaced by spline functions. The developed algorithm generates smooth motion trajectories with two times continuously differentiable curvature avoiding obstacles placed in the workspace. It can be used for autonomous robot path planning or transport problems. The spline based trajectory generation gives us continuous, smooth and optimized path trajectories. Simulation and experimental results demonstrate the effectiveness of the proposed method.info:eu-repo/semantics/publishedVersio

A snake-based scheme for path planning and control with constraints by distributed visual sensors

YesThis paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robot’s non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.Royal Society, Natural Science Funding Council (China

A Novel Obstacle Avoidance Approach For Nonholonomic Ground Vehicle Autonomy

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2012Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2012Bu çalışmada, holonom olmayan bir kara taşıtı için, “Boşluğu Takip Et” (BTE) isimli yeni bir engelden kaçma ve çarpışma önleme metodu geliştirilmiştir. Bu metod, probleme yeni bir çözüm getirmektedir ve diğer metodlara göre çeşitli avantajlara sahiptir. Geliştirilen metodun, benzer metodlarla yapılan karşılaştırılmalar sonucunda, daha güvenli güzergahlarla sonuçlandığı gösterilmiştir. Ayrıca BTE, yapay potansiyel alanlar (YPA) metodu ve bu tabanda çalışan diğer tüm metodların ortak problemi olan lokal minimum probleminden bağımsızdır. BTE’nin bir diğer özelliği, aracın holonom olmayan kısıtlarını ve sensörlerin görüş açısı kısıtlarını da göz önünde bulundurabilmesidir. BTE’nin tamamen reaktif yapısı sayesinde, yalnızca durağan engellerden değil, hareketli engellerden de rahatlıkla sıyrıldığı da tez içerisinde gösterilmiştir. Son olarak, sadece bir ayar parametresine sahip olduğu için, kullanımı da oldukça kolaydır. Engelden kaçınmak için, yalnızca aracın yönelim açısının belirlenmesinin yetmeyeceği düşüncesinden hareketle, aracın engelli bir ortamda hız planlaması için de yeni bir metod geliştirilmiştir. İki adet bulanık çıkarım sisteminin (BÇS) tasarlanmasıyla oluşturulan bu yeni yapı, engellerin oluşturduğu risk durumuna ve aracın yönelim açısına bağlı olarak çalışır. Planlanan hızın takip edilmesi için de yine bulanık mantık kullanılarak yeni bir alt seviye hız kontrolörü tasarlanmıştır. Tasarlanan tüm metodlar, literatürdeki bezerleriyle simülasyon ortamında karşılaştırılmış ve sonuçları gösterilmiştir. Geliştirilen her üç yeni metod, tam otonom kara taşıtı (OKT) üzerinde deneysel olarak da test edilerek sonuçların başarılı olduğu gösterilmiştir. Simülasyonlarda kullanılan araç modelleri ve deneysel düzeneğin tasarımı da tez içerisinde ayrı bölümler halinde anlatılmıştır.In this study, a new obstacle avoidance algorithm “Follow the Gap Method” (FGM) is designed for nonholonomic ground vehicle autonomy. The proposed method brings a new solution to the problem and has several advantages compared to previous methods. Fisrstly, the FGM results in safer trajectories than other compared approaches. This new method is free from local minima which is a big problem for Artificial Potential Fields (APF) and similar methods. Taking into consideration the field of view and the nonholonomic constraints of the vehicle is another advantage of the FGM. Through the purely reactive nature of the FGM, it is shown that not only the static but also the dynamic obstacles are avoided. Besides these, it is easy to tune the algorithm with only one tuning parameter. Vehicle speed is as important as the appropriate steering angle for obstacle avoidance. From this view point, a new speed planning method is designed for the vehicle. Two fuzzy inference systems operate depending on the danger level of the obstacles and the steering angle. In order to track the speed commands from the speed planner, a new low level speed controller is designed based on fuzzy rules. All designed methods are simulated and compared with other methods in literature. The designed methods are also tested experimentally using the real unmanned ground vehicle (UGV) platform and it is shown that experimental results are successful too. The used models for the simulations and designed experimental platform are illustrated in separated sections throughout the thesis.DoktoraPh

A non-holonomic, highly human-in-the-loop compatible, assistive mobile robotic platform guidance navigation and control strategy

The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal. Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic. This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments

Wireless mosaic eyes based robot path planning and control. Autonomous robot navigation using environment intelligence with distributed vision sensors.

As an attempt to steer away from developing an autonomous robot with complex centralised intelligence, this thesis proposes an intelligent environment infrastructure where intelligences are distributed in the environment through collaborative vision sensors mounted in a physical architecture, forming a wireless sensor network, to enable the navigation of unintelligent robots within that physical architecture. The aim is to avoid the bottleneck of centralised robot intelligence that hinders the application and exploitation of autonomous robot. A bio-mimetic snake algorithm is proposed to coordinate the distributed vision sensors for the generation of a collision free Reference-snake (R-snake) path during the path planning process. By following the R-snake path, a novel Accompanied snake (A-snake) method that complies with the robot's nonholonomic constraints for trajectory generation and motion control is introduced to generate real time robot motion commands to navigate the robot from its current position to the target position. A rolling window optimisation mechanism subject to control input saturation constraints is carried out for time-optimal control along the A-snake. A comprehensive simulation software and a practical distributed intelligent environment with vision sensors mounted on a building ceiling are developed. All the algorithms proposed in this thesis are first verified by the simulation and then implemented in the practical intelligent environment. A model car with less on-board intelligence is successfully controlled by the distributed vision sensors and demonstrated superior mobility