Combining Programming by Demonstration with Path Optimization and Local Replanning to Facilitate the Execution of Assembly Tasks

Gorjup, Gal; Kontoudis, George P.; Dwivedi, Anany; Gao, Geng; Matsunaga, Saori; Mariyama, Toshisada; MacDonald, Bruce; Liarokapis, Minas

doi:10.1109/smc42975.2020.9282991

Cited by 3 publications

(1 citation statement)

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“…Secondly, the interaction state is divided, which clearly shows the proportion of time consumed in the experiment, and readers can further optimize certain states. There have been some similar human-computer cooperation studies in which humans control robots through a data glove and the robot's complete trajectory correction and obstacle avoidance [50]. In comparison, data glove stability may be better; however, it is inconvenient to wear.…”

Section: Experimental Time Consumptionmentioning

confidence: 99%

Human–Robot Collaborative Assembly Based on Eye-Hand and a Finite State Machine in a Virtual Environment

Zhao

Chen

et al. 2021

Applied Sciences

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With the development of the global economy, the demand for manufacturing is increasing. Accordingly, human–robot collaborative assembly has become a research hotspot. This paper aims to solve the efficiency problems inherent in traditional human-machine collaboration. Based on eye–hand and finite state machines, a collaborative assembly method is proposed. The method determines the human’s intention by collecting posture and eye data, which can control a robot to grasp an object, move it, and perform co-assembly. The robot’s automatic path planning is based on a probabilistic roadmap planner. Virtual reality tests show that the proposed method is more efficient than traditional methods.

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Section: Experimental Time Consumptionmentioning

confidence: 99%