Recent years have witnessed the prosperity of robots and in order to support consensus and cooperation for multi- robot system, wireless communications and networking among robots and the infrastructure have become indispensable. In this technical note, we first provide an overview of the research contributions on communication-aware motion planning (CAMP) in designing wireless-connected robotic networks (WCRNs), where the degree-of-freedom (DoF) provided by motion and communication capabilities embraced by the robots have not been fully exploited. Therefore, we propose the framework of joint communication-motion planning (JCMP) as well as the architecture for incorporating JCMP in WCRNs. The proposed architecture is motivated by the observe-orient-decision-action (OODA) model commonly adopted in robotic motion control and cognitive radio. Then, we provide an overview of the orient module that quantify the connectivity assessment. Afterwards, we highlight the JCMP module and compare it with the conventional communication-planning, where the necessity of the JCMP is validated via both theoretical analysis and simulation results of an illustrative example. Finally, a series of open problems are discussed, which picture the gap between the state-of-the-art and a practical WCRN.
Recent years have witnessed the evolution of robotics and great industrial academic efforts. As the robots interact with the physical and social environments, considerable research contributions have been devoted to robotic sensing, cognition, motion path planning and control @cite_37 . A multi-robot system aims at achieving challenging tasks or significantly improving mission performance compared with a single robot, which demands consensus and cooperation among robots @cite_11 . Therefore, maintaining the connectivity quality for information exchange among robots becomes vital. As mobile robots are less likely to be connected via wires, the wireless communications and networking among robots and the infrastructure would play an crucial role and the wireless-connected robotic networks (WCRNs) are very likely to be incorporated into the next-generation communication networks.
@cite_37 @cite_11
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Future life pictures humans having intelligent humanoid robotic systems taking part in their everyday life. Thus researchers strive to supply robots with an adequate artificial intelligence in order to achieve a natural and intuitive interaction between human being and robotic system. Within the German Humanoid Project we focus on learning and cooperating multimodal robotic systems. In this paper we present a first cognitive architecture for our humanoid robot: The architecture is a mixture of a hierarchical three-layered form on the one hand and a composition of behaviour-specific modules on the other hand. Perception, learning, planning of actions, motor control, and human-like communication play an important role in the robotic system and are embedded step by step in our architecture This paper presents HiDDeN, a high-level distributed architecture for multi-robot cooperation. HiDDeN aims at controlling a team of heterogeneous robots in environments with uncertain communications. It relies on a mission plan defined as an instantiated HTN, i.e. a hierarchical decomposition of robots' tasks. This hierarchical structure also benefits to plan repair operations in case of failure detections. This repair is made as local as possible, in order to avoid unnecessary communications between robots. Traditionally, motion planning involved navigating one robot from source to goal for accomplishing a task. Now, tasks mostly require movement of a team of robots to the goal site, requiring a chain of robots to reach the desired goal. While numerous efforts are made in the literature for solving the problems of motion planning of a single robot and collective robot navigation in isolation, this paper fuses the two paradigms to let a chain of robot navigate. Further, this paper uses SLAM to first make a static map using a high-end robot, over which the physical low-sensing robots run. Deliberative Planning uses A* algorithm to plan the path. Reactive planning uses the Potential Field Approach to avoid obstacles and stay as close to the initial path planned as possible. These two algorithms are then merged to provide an algorithm that allows the robot to reach its goal via the shortest path possible while avoiding obstacles. The algorithm is further extended to multiple robots so that one robot is followed by the next robot and so on, thus forming a chain. In order to maintain the robots in a chain form, the Elastic Strip model is used. The algorithm proposed successfully executes the above stated when tested on Amigobot robots in an office environment using a map made by the Pioneer LX robot. The proposed algorithm works well for moving a group of robots in a chain in a mapped environment. Nowadays, we can no longer imagine that Internet can be considered just a network of computers. We also have to state that it's becoming even more a network of things. With this in mind, this paper introduces a long range Internet connected robot teleoperation system based on Internet of Things (IoT). The aim is to support operators during remote teleoperation of robotic systems in situations in which the remote control devices loose the connection with the on-board receivers. This situation can occur either due to the lost of the line-of-sight or due to possible damages of the devices. IoT allows to connect remote and mobile things or machines. It also assets through the use of wireless communications and low-cost sensors, computing and storage devices. Approaches based on IoT have been already applied in traffic monitoring, smart homes, smart parking management, vehicle tracking system and other industrial applications. We used the system to control a mobile robot without range barriers provided that the robot and the remote control device must be connected to the Internet.