Learning landing control of an indoor blimp robot for self-energy recharging

We report on learning landing control for the self-energy recharging of indoor blimp robots. Indoor blimp robots have potential applications in monitoring, surveillance, and entertainment. It might be necessary for blimp robots to fly for a long time to achieve these tasks. Since blimp robots cannot have a heavy battery, it is difficult to fly for long time. Therefore, we solved this problem by developing self-energy recharging control, i.e., docking to an energy charging station. We call it landing control. We introduce a way to learn landing control to tackle an unstable flying condition. The results of experiments show the effectiveness of the landing control. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Cooperative control of multiple neural networks for an indoor blimp robot

We report on the cooperative control of multiple neural networks for an indoor blimp robot. In our research group, the indoor blimp robot has been studied to achieve various flying robot applications. The objective of this article is to propose a robust controller that can adapt to mechanical accidents such as the breakdown of propellers. In our proposed method, each propeller thrust is independently calculated by a small neural network. We confirm the advantage of the proposed method against the control by a single large neural network. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Flying over the reality gap: From simulated to real indoor airships

Because of their ability to naturally float in the air, indoor airships (often called blimps) constitute an appealing platform for research in aerial robotics. However, when confronted to long lasting experiments such as those involving learning or evolutionary techniques, blimps present the disadvantage that they cannot be linked to external power sources and tend to have little mechanical resistance due to their low weight budget. One solution to this problem is to use a realistic flight simulator, which can also significantly reduce experimental duration by running faster than real time. This requires an efficient physical dynamic modelling and parameter identification procedure, which are complicated to develop and usually rely on costly facilities such as wind tunnels. In this paper, we present a simple and efficient physics-based dynamic modelling of indoor airships including a pragmatic methodology for parameter identification without the need for complex or costly test facilities. Our approach is tested with an existing blimp in a vision-based navigation task. Neuronal controllers are evolved in simulation to map visual input into motor commands in order to steer the flying robot forward as fast as possible while avoiding collisions. After evolution, the best individuals are successfully transferred to the physical blimp, which experimentally demonstrates the efficiency of the proposed approach. Jean-Christophe Zufferey and Alexis Guanella contributed equally to this work.     

mxAutomation接口的机器人通信协议开发

在智能变电站中,带电检修机器人对隔离断路器进行带电检修的核心技术是实现对2台(工业)机器人的控制.变电站中强电磁场的干扰对机器人控制的可靠性提出了难题.因此,需要制定相应的上位机工控机(IPc)与控制机器人的可编程逻辑控制器(PLC)之间的通信协议,以实现两者之间可靠的通信,从而实现IPC对机器人的可靠控制.     

Robotic assembly automation using robust compliant control

Industrial robots used to perform assembly applications are still a small portion of total robot sales each year. One of the main reasons is that it is difficult for conventional industrial robots to adapt to any sort of change. This paper proposes a robust control strategy to perform an assembly task of inserting a printed circuit board (PCB) into an edge connector socket using a SCARA robot. The task is very challenging because it involves compliant manipulation in which a substantial force is needed to accomplish the insertion operation and there are some dynamic constraints from the environment. Therefore, a robust control algorithm is developed and used to perform the assembly process. The dynamic model of the robotic system is developed and the dynamic parameters are identified. Experiments were performed to validate the proposed method. Experimental results show that the robust control algorithm can deal with parameter uncertainties in the dynamic model, thus achieve better performance than the model based control method. An abnormal case is also investigated to demonstrate that the robust compliant control method can deal with the abnormal situation without damaging the system and assembly parts, while pure position control method may cause damages. This strategy can also be used in other similar assembly processes with compliant applications.     

Motion estimation of indoor robot based on image sequences and improved particle filter

Robot motion estimation is fundamental in most robot applications such as robot navigation, which is an indispensable part of future internet of things. Indoor robot motion estimation is difficult to be resolved because GPS (Global Positioning System) is unavailable. Vision sensors can provide larger amount of image sequences information compared with other traditional sensors, but it is subject to the changes of light. In order to improve the robustness of indoor robot motion estimation, an enhanced particle filter framework is constructed: firstly, motion estimation was implemented based on the distinguished indoor feature points; secondly, particle filter method was utilized and the least square curve fitting was inserted into the particle resampling process to solve the problem of particle depletion. The various experiments based on real robots show that the proposed method can reduce the estimation errors greatly and provide an effective resolution for the indoor robot localization and motion estimation.

     

利用事件和期限驱动对机器人延时的优化

随着科技的进步,机器人领域得到了飞速发展,为了更好地让机器人适应复杂工作环境,需要进一步提高机器人的感知性能。大多数机器人采用视觉作为感知手段。但由于图像中包含大量数据以及处理这些数据需要花费大量时间,导致了机器人有显著的延时,从而导致机器人性能的下降。因此,为了解决这一问题,提出了一种基于期限驱动和事件驱动控制方法,该方法的核心是把基于模型的控制设计方法的思想应用到基于视觉的自定位算法的机器人运动控制中。同时考虑了一种简单的基于随机样本一致性的定位算法的延时情况。实验结果证明,提出的期限驱动和事件驱动控制设计明显优于传统的周期控制。     

A rescue robot system for collecting information designed for ease of use — a proposal of a rescue systems concept

A remote controlled robot for collecting information in disasters, e.g. earthquakes, is one of most effective applications of robots, because it is very dangerous for human beings to locate survivors in collapsed buildings and, in addition, small robots can move into narrow spaces to find survivors. However, previous rescue systems that use robots have a significant problem — a shortage of operators. In catastrophic disasters, in order to save victims, we must explore wide areas within a limited time. Thus, many rescue robots should be employed simultaneously. However, human interfaces of previous rescue robots were complicated, so that well-trained professional operators were needed to operate the robots and, thus, to use many rescue robots, many professional operators were required. However, in such catastrophic disasters it is difficult to get many professional operators together within a short time. In this paper we address the problem and propose a concept of rescue team organization in which professional rescue staff and volunteer staff work together for handling a catastrophic disaster. We point out the necessity for rescue robots which can be operated easily by non-professional volunteer staff. To realize a rescue robot which can be operated easily, we propose a rescue robot system which has a human interface seen in typical, everyday vehicles and a snake-like robot which has mechanical intelligence. We have demonstrated the validity and the effectiveness of the proposed concept by developing a prototype system.     

Robots in space - a survey

The paper tries to outline the state of the art in space robotics. It discusses the technologies used in ROTEX, the first remotely controlled space robot which flew with the shuttle Columbia in April 1993, but it also gives a review of the major space robot projects envisioned by different nations for the next decade. The mechatronics and dynamics aspects of space robots including free-flying systems are briefly discussed. Broader attention is given to the telerobotic and teleoperational control loop structures, including predictive delay-compensating graphics simulation. The paper finally tries to emphasize that by task-level programming (involving 'learning by showing' on a high level) future space robots will be powerful tools for scientists and ground operators which are not robot specialists. The tele-sensor programming concept of ROTEX was a first step in this direction. We plead for flying a variety of space robot systems in the near future in order to enhance experience with and confidence in these technologies as quickly as possible.     

Development of a flexible autonomous robot without sensors or controllers

Recently, various robots with many degrees of freedom, such as rescue robots and domestic robots, have been developed and used in practical applications. It is difficult to control such robots autonomously in real environments, because in order to control the many degrees of freedom, we have to observe many states, calculate huge amounts of information, and operate many actuators. In this study, we consider a flexible robot without sensors or controllers that can determine the inclination of a slope and climb up the slope. In order to demonstrate the effectiveness of the proposed framework, we have developed a prototype robot and conducted experiments. The result indicates that the robot could determine the inclination and climb up a gentle slope autonomously. Thus, we have realized an autonomous robot that has no explicit sensors or controllers.