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1.
《Mechatronics》2022
A wide range of dangerous and special tasks have witnessed the applications of wall-climbing robots, but they still cannot adapt well torough or sloping walls. This paper proposes a 6-DOF (degree of freedom) humanoid wall-climbing robot (HWCR) based on the principle of negative pressure suction. HWCR has the advantages of flexible adsorption feet, strong adaptability, strong anti-subversion performance, and high friction to the wall. We deduce mechanics formulas and carry out a parametric design of the foot structure so that it can meet the requirement of robot wall climbing. We use Fluent to analyze the flow field of the adsorption foot and determine the motor speed that can provide a reliable adsorption force. Using the D-H matrix to plan gait, we also design a compound cycloid-based foot trajectory to reduce the impact between the HWCR and the wall. Experiments on the uneven wall and sloping wall show that the vehicle can walk with an ideal gait, and the resistance value of the servo on each joint is much lower than the critical value, which ensures the smooth movement of the HWCR. 相似文献
2.
《Mechatronics》2022
This paper considers the shared path following control of an unmanned ground vehicle by a single person. A passive measure of human intent is used to blend the human and machine inputs in a mixed initiative approach. The blending law is combined with saturated super-twisting sliding mode speed and heading controllers, so that exogenous disturbances can be counteracted via equivalent control. It is proven that when the proposed blending law is used, the combined control signals from both the human and automatic controller respect the actuator magnitude constraints of the machine. To demonstrate the approach, shared control experiments are performed using an unmanned ground vehicle, which follows a lawn mower pattern shaped path. 相似文献
3.
针对爬壁清洗机器人越障时,负压装置的吸附力下降导致吸附不稳定的问题,设计了一种旋翼负压混合吸附工作的多边形履带清洗机器人,并对爬行稳定性及越障性能进行了动力学分析。首先根据机器人爬壁的运动原理,建立机器人沿玻璃幕墙上的动力学模型,计算出电机理论驱动力矩;其次分析机器人在跨越障碍过程中的运动模型,结合与壁面接触的实际受力状态,对越障过程中关键阶段的本体倾翻、滑移两种失效形式进行运动学和动力学分析;然后根据玻璃幕墙实际的障碍高度,确定多边形履带的参数和理论驱动力矩的大小,并研制了实验样机进行爬行和越障试验,结果表明所设计的机器人具有良好的越障性能。 相似文献
4.
面对三维空间移动机器人从起始点到终止点的最短路径问题,提出一种新型的边缘点树启发式搜索(TreeEP)算法,该方法将地图空间进行密度可调的三维离散化处理,根据障碍安全距离筛选出障碍物的可靠边缘点信息,再利用树扩散架构选出最能引导搜索方向的潜力点进行扩散搜索,最终得出最短路径。提出局部调整策略,得到改进的Tree-EP算法。实验结果表明,在带障碍复杂地形最短路径搜索应用中,提出的Tree-EP算法与已有方法相比,能找到更短的移动路径。 相似文献
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AbstractIn recent years, to prevent accidents and disaster are desired by implementing maintenance and management of facilities, such as conducting periodic inspections with appropriate frequency at plants. However, because the dangerous materials such as flammable gas and explosives is used in a plant, and there are many dangerous places in a plant such as high-temperature environment and high places and narrow spaces, it is desirable to use a remote-controlled robot for safety work and short inspections. Against this background, the Disaster Robotics Category-Plant Disaster Prevention Challenge was held in Japan at the World Robot Summit 2018. Our team was ranked 3rd in this competition, because our strategy of ‘inspection and investigation in cooperation with UGV and UAV’ was effective. In this paper, the competition contents of World Robot Summit 2018 and the robot inspection system that we are studying are explained. And what kind of strategy was challenged and result for these given competition tasks by using our robot system are introduced. And the lessons learned such as advantages and issues in UGV and UAV collaboration work at this competition are described for evaluate a robot investigation system for disaster response and inspection work at plants. 相似文献
8.
In an environment where robots coexist with humans, mobile robots should be human-aware and comply with humans' behavioural norms so as to not disturb humans' personal space and activities. In this work, we propose an inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision. In this method, the planning process of time-dependent A* is regarded as a Markov decision process and the cost function of the time-dependent A* is learned using the inverse reinforcement learning via capturing humans' demonstration trajectories. With this method, a robot can plan a path that complies with humans' behaviour patterns and the robot's kinematics. When constructing feature vectors of the cost function, considering the local vision characteristics, we propose a visual coverage feature for enabling robots to learn from how humans move in a limited visual field. The effectiveness of the proposed method has been validated by experiments in real-world scenarios: using this approach robots can effectively mimic human motion patterns when avoiding pedestrians; furthermore, in a limited visual field, robots can learn to choose a path that enables them to have the larger visual coverage which shows a better navigation performance. 相似文献
9.
针对移动机器人在海水环境中的三维路径规划问题容易陷入局部最优和收敛慢等瑕疵,根据三维环境全局信息来改进蚁群算法以提高实时性和收敛速度。改进蚁群算法的启发函数,采用局部信息和全局信息结合动态地改进信息素更新方式,以及根据三维空间中路径的平坦程度和光滑度二阶微分分别增加了一阶微分和二阶微分来再次修改信息素更新规则。仿真对比实验结果显示改进后的蚁群算法克服了收敛速度慢、容易陷入局部最优的缺点。 相似文献
10.
This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large‐scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi‐Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size. 相似文献