Benchmarking and optimization of robot motion planning with motion planning pipeline

Liu, Shuai; Liu, Pengcheng

doi:10.1007/s00170-021-07985-5

Cited by 16 publications

(8 citation statements)

References 35 publications

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“…Liu aims the optimization of the motion planner algorithm using a motion planning pipeline and a planning request adapter, for example, to optimize the sample-based motion planning algorithm. Experimental results show that the optimized algorithm increases the planning time but significantly improves the efficiency [10]. e research results of the above scholars are only partially relevant and suggestive to the research topic of this study.…”

Section: Related Workmentioning

confidence: 68%

Simulation of Multimedia Visual Image Motion Track Marking Based on Artificial Bee Colony Algorithm

Chen

2022

Mathematical Problems in Engineering

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With the rapid development of electronic technology, network technology, and multimedia processing technology, people pay more and more attention to the surrounding environment. Paying attention to and handling emergencies have also become one of the main points of attention. Through the combination of multimedia and monitoring system, the collected image data are processed and integratedly controlled by the computer platform, and an intelligent monitoring system for traffic road safety can be obtained. Due to the advantages of multimedia visual image motion trajectory identification technology in road traffic safety, it can effectively prevent the chaos and influence caused by humans in chaotic situations, making it widely used. By identifying the motion trajectories of different objects, road emergencies can be effectively prevented and countermeasures can be established. Based on this, this study proposes the artificial bee colony (ABC) algorithm to identify the motion trajectory in the visual image, but the standard ABC algorithm is too slow to converge in the later stage of trajectory recognition. Therefore, this study is based on the standard ABC algorithm. The trajectory recognition simulation shows that the optimized algorithm accelerates the convergence speed and the ability of the global optimal solution in the trajectory recognition process. Then, the optimized ABC algorithm is used to identify the multimedia visual image trajectory. The experiment shows that the average correct rate of feature extraction is also about 98%. The data identification results also show that the optimized ABC algorithm fits the real trajectory better in the trajectory identification. The running time of the algorithm is shorter than the running time of other comparison algorithms, which fully shows the accuracy and superiority of the algorithm in this study.

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Section: Related Workmentioning

confidence: 68%

Simulation of Multimedia Visual Image Motion Track Marking Based on Artificial Bee Colony Algorithm

Chen

2022

Mathematical Problems in Engineering

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“…The proposed data-driven controller adjusts the robot's Cartesian velocity to prevent losing contact with the strawberry stem during the pushing task execution based on the sensory feedback from a camera-based tactile finger. Off-the-shelf motion planning libraries [233,234] lack integrating tactile feedback in problem formulation, such as the approaches in [28,29,150] for more robust closed-loop motion planning.…”

Section: Motion Planningmentioning

confidence: 99%

Tactile-Sensing Technologies: Trends, Challenges and Outlook in Agri-Food Manipulation

Mandil,

Rajendran,

Nazari

et al. 2023

Sensors

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Tactile sensing plays a pivotal role in achieving precise physical manipulation tasks and extracting vital physical features. This comprehensive review paper presents an in-depth overview of the growing research on tactile-sensing technologies, encompassing state-of-the-art techniques, future prospects, and current limitations. The paper focuses on tactile hardware, algorithmic complexities, and the distinct features offered by each sensor. This paper has a special emphasis on agri-food manipulation and relevant tactile-sensing technologies. It highlights key areas in agri-food manipulation, including robotic harvesting, food item manipulation, and feature evaluation, such as fruit ripeness assessment, along with the emerging field of kitchen robotics. Through this interdisciplinary exploration, we aim to inspire researchers, engineers, and practitioners to harness the power of tactile-sensing technology for transformative advancements in agri-food robotics. By providing a comprehensive understanding of the current landscape and future prospects, this review paper serves as a valuable resource for driving progress in the field of tactile sensing and its application in agri-food systems.

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“…Yet, with the increasingly complex operating scenarios of indoor robots, traditional navigation methods based on metric maps have been unable to meet the needs of human beings [7]. In the future, the goal of robots is to operate in a human-centered home or industrial environment [12,13]. Robots should process the ability to perceive and understand surrounding environments like humans, such as distinguishing rooms and corridors in the environment.…”

Section: Introductionmentioning

confidence: 99%

Monocular camera and laser based semantic mapping system with temporal-spatial data association for indoor mobile robots

Zuo

Xuan

Zhou

2023

Multimed Tools Appl

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In the future, the goal of service robots is to operate in human-centric indoor environments, requiring close cooperation with humans. In order to enable the robot to perform various interactive tasks, it is necessary for robots to perceive and understand environments from a human perspective. Semantic map is an augmented representation of the environment, containing both geometric information and high-level qualitative features. It can help the robot to comprehensively understand the environment and bridge the gap in human-robot interaction. In this paper, we propose a unified semantic mapping system for indoor mobile robots. This system utilizes the techniques of scene classification and object detection to construct semantic representations of indoor environments by fusing the data of a camera and a laser. In order to improve the accuracy of semantic mapping, the temporal-spatial correlation of semantics is leveraged to realize data association of semantic maps. Also, the proposed semantic mapping system is scalable and portable, which can be applied to different indoor scenarios. The proposed system was evaluated with collected datasets captured in indoor environments. Extensive experimental results indicate that the proposed semantic mapping system exhibits great performance in the robustness and accuracy of semantic mapping.

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Benchmarking and optimization of robot motion planning with motion planning pipeline

Cited by 16 publications

References 35 publications

Simulation of Multimedia Visual Image Motion Track Marking Based on Artificial Bee Colony Algorithm

Simulation of Multimedia Visual Image Motion Track Marking Based on Artificial Bee Colony Algorithm

Tactile-Sensing Technologies: Trends, Challenges and Outlook in Agri-Food Manipulation

Monocular camera and laser based semantic mapping system with temporal-spatial data association for indoor mobile robots

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