Autonomous Navigation for Unmanned Aerial Systems - Visual Perception and Motion Planning

L'abstract è presente nell'allegato / the abstract is in the attachmen

The ILIAD Safety Stack: Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots

Safe yet efficient operation of professional service robots within logistics or production in human-robot shared environments requires a flexible human-aware navigation stack. In this manuscript, we propose the ILIAD safety stack comprising software and hardware designed to achieve safe and efficient motion specifically for industrial vehicles with nontrivial kinematics The stack integrates five interconnected layers for autonomous motion planning and control to enable short- and long-term reasoning. The use-case scenario tested requires an autonomous industrial forklift to safely navigate among pick-and-place locations during normal daily activities involving human workers. Our test-bed in the real world consists of a three-day experiment in a food distribution warehouse. The evaluation is extended in simulation with an ablation study of the impact of different layers to show both the practical and the performance-related impact. The experimental results show a safer and more legible robot when humans are nearby with a trade-off in task efficiency, and that not all layers have the same degree of impact in the system

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

A survey of formation control and motion planning of multiple unmanned vehicles

The increasing deployment of multiple unmanned vehicles systems has generated large research interest in recent decades. This paper therefore provides a detailed survey to review a range of techniques related to the operation of multi-vehicle systems in different environmental domains, including land based, aerospace and marine with the specific focuses placed on formation control and cooperative motion planning. Differing from other related papers, this paper pays a special attention to the collision avoidance problem and specifically discusses and reviews those methods that adopt flexible formation shape to achieve collision avoidance for multi-vehicle systems. In the conclusions, some open research areas with suggested technologies have been proposed to facilitate the future research development

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics

Path Planning Algorithms for Autonomous Mobile Robots

This thesis work proposes the development and implementation of multiple different path planning algorithms for autonomous mobile robots, with a focus on differentially driven robots. Then, it continues to propose a real-time path planner that is capable of finding the optimal, collision-free path for a nonholonomic Unmanned Ground Vehicle (UGV) in an unstructured environment. First, a hybrid A* path planner is designed and implemented to find the optimal path; connecting the current position of the UGV to the target in real-time while avoiding any obstacles in the vicinity of the UGV. The advantages of this path planner are that, using the potential field techniques and by excluding the nodes surrounding every obstacles, it significantly reduces the search space of the traditional A* approach; it is also capable of distinguishing different types of obstacles by giving them distinct priorities based on their natures and safety concerns. Such an approach is essential to guarantee a safe navigation in the environment where humans are in close contact with autonomous vehicles. Then, with consideration of the kinematic constraints of the UGV, a smooth and drivable geometric path is generated. Throughout the whole thesis, extensive practical experiments are conducted to verify the effectiveness of the proposed path planning methodologies

System Design, Motion Modelling and Planning for a Recon figurable Wheeled Mobile Robot

Over the past ve decades the use of mobile robotic rovers to perform in-situ scienti c investigations on the surfaces of the Moon and Mars has been tremendously in uential in shaping our understanding of these extraterrestrial environments. As robotic missions have evolved there has been a greater desire to explore more unstructured terrain. This has exposed mobility limitations with conventional rover designs such as getting stuck in soft soil or simply not being able to access rugged terrain. Increased mobility and terrain traversability are key requirements when considering designs for next generation planetary rovers. Coupled with these requirements is the need to autonomously navigate unstructured terrain by taking full advantage of increased mobility. To address these issues, a high degree-of-freedom recon gurable platform that is capable of energy intensive legged locomotion in obstacle-rich terrain as well as wheeled locomotion in benign terrain is proposed. The complexities of the planning task that considers the high degree-of-freedom state space of this platform are considerable. A variant of asymptotically optimal sampling-based planners that exploits the presence of dominant sub-spaces within a recon gurable mobile robot's kinematic structure is proposed to increase path quality and ensure platform safety. The contributions of this thesis include: the design and implementation of a highly mobile planetary analogue rover; motion modelling of the platform to enable novel locomotion modes, along with experimental validation of each of these capabilities; the sampling-based HBFMT* planner that hierarchically considers sub-spaces to better guide search of the complete state space; and experimental validation of the planner with the physical platform that demonstrates how the planner exploits the robot's capabilities to uidly transition between various physical geometric con gurations and wheeled/legged locomotion modes