Abstract
Increasing requirements for the safety of human-robot interaction and the cost-effectiveness of collision detection rapidly promote the development of collision detection technology without torque sensors. To address nonlinear disturbance factors in collision detection that may cause unstable or even incorrect detection, this paper proposed a research strategy that considered the friction as the disturbance term in manipulator motion for the collision detection. The manipulator joint disturbance model was established based on the LuGre dynamic friction model, and the external torque observer was designed based on the generalized momentum. Then, the friction measurement was realized using the external torque observer, and the model parameters were identified through the genetic algorithm. The collision detection can be reduced errors after the friction model by compensating the disturbance and can be applicable to variable working conditions. Finally, the accuracy of the constructed disturbance model and the performance of the proposed collision detection method were validated by the experimental studies.
Highlights
With the expansion of robot applications ranging from industrial environments to home services, medical treatments, and space exploration, human-robot collaboration has become a hot topic [1,2].Compared with industrial robots that can only work in the fence, collaborative robots can share working spaces with humans
The International Organization for Standardization (ISO) has proposed relevant technical standards about collaborative robot safety, including safety specifications, risk assessments, and so on, to minimize the potential risk caused by human-robot collision [4]
According to the LuGre friction model obtained by the identification, the friction of each operating manipulator joint can be calculated in real time and be employed to compensate the external torque observed by the external torque observer
Summary
With the expansion of robot applications ranging from industrial environments to home services, medical treatments, and space exploration, human-robot collaboration has become a hot topic [1,2]. The traditional methods applied for the collision detection of collaborative robot often adopt the scheme of installing an external sensor, such as a joint torque sensor [9,10]. Cho et al proposed a new collision detection algorithm by observing the speed of external torque changes based on the data of the joint torque sensor. The installation of a torque sensor could guarantee the safety of human and robot during the collaboration and make collision detection applicable to more complex occasions. This method has the disadvantages of increasing the complexity of joint design, limiting the working performance, and increasing the manufacturing cost.
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