A dynamic obstacle avoidance method for collaborative robots based on trajectory optimization

Cobot Pub Date : 2023-12-14 DOI:10.12688/cobot.17673.1
Weizong Ge, Hongyu Chen, Hongtao Ma, Liuhe Li, Ming Bai, Xilun Ding, Kun Xu
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引用次数: 0

Abstract

Background Collision detection is crucial in the design of robot planning algorithms. Efficient distance sensors can provide high-resolution environmental collision information to the robot's planning algorithm. However, this also leads to the robot obstacle avoidance performance being limited by the performance of the sensors. Therefore, it becomes a challenge to achieve efficient obstacle avoidance with low-resolution environmental information. Methods First, we use a self-developed capacitive array non-contact distance sensing flexible surface for sensing the proximity of colliding objects. Second, we designed an optimization-based dynamic obstacle avoidance planning algorithm, using only the minimum separation distance and penetration direction as obstacle avoidance information, and referring to the idea of stochastic gradient descent, using real-time collision avoidance information to do single-step optimization adjustment. Results We conducted the dynamic obstacle avoidance test experiment by connecting the electronic skin to the semi-physical prototype and the full physical prototype. The experiments show that efficient dynamic obstacle avoidance can be realized under the maximum effective range of only 5~7cm, and it has strong flexibility to avoid different shapes of dynamic obstacles in a non-contact manner, and finally arrive at the target position. Conclusions In this paper, an online obstacle avoidance planning algorithm designed based on an optimization method that is not limited to the shape of obstacles is proposed, and the effectiveness of the algorithm is verified by physical experiments in combination with a self-developed flexible distance sensing surface. It is of great significance for the safe operation of human-robot interaction in collaborative robots.
基于轨迹优化的协作机器人动态避障方法
背景碰撞检测对机器人规划算法的设计至关重要。高效的距离传感器可以为机器人的规划算法提供高分辨率的环境碰撞信息。然而,这也导致机器人的避障性能受到传感器性能的限制。因此,如何利用低分辨率的环境信息实现高效避障成为了一个挑战。方法 首先,我们使用自主研发的电容阵列非接触式距离感应柔性表面来感应碰撞物体的距离。其次,我们设计了一种基于优化的动态避障规划算法,仅使用最小分离距离和穿透方向作为避障信息,并参考随机梯度下降的思想,利用实时避撞信息进行单步优化调整。结果 我们将电子皮肤与半实物原型和全实物原型连接,进行了动态避障测试实验。实验表明,在最大有效距离仅为 5~7cm 的情况下,可以实现高效的动态避障,并且具有很强的灵活性,能以非接触的方式避开不同形状的动态障碍物,最终到达目标位置。结论 本文提出了一种基于优化方法设计的、不受障碍物形状限制的在线避障规划算法,并结合自主研发的柔性距离传感面,通过物理实验验证了该算法的有效性。这对协作机器人的人机交互安全运行具有重要意义。
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来源期刊
Cobot
Cobot collaborative robots-
自引率
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期刊介绍: Cobot is a rapid multidisciplinary open access publishing platform for research focused on the interdisciplinary field of collaborative robots. The aim of Cobot is to enhance knowledge and share the results of the latest innovative technologies for the technicians, researchers and experts engaged in collaborative robot research. The platform will welcome submissions in all areas of scientific and technical research related to collaborative robots, and all articles will benefit from open peer review. The scope of Cobot includes, but is not limited to: ● Intelligent robots ● Artificial intelligence ● Human-machine collaboration and integration ● Machine vision ● Intelligent sensing ● Smart materials ● Design, development and testing of collaborative robots ● Software for cobots ● Industrial applications of cobots ● Service applications of cobots ● Medical and health applications of cobots ● Educational applications of cobots As well as research articles and case studies, Cobot accepts a variety of article types including method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.
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