Abstract
The new paradigm of human-robot collaboration has led to the creation of shared work environments in which humans and robots work in close contact with each other. Consequently, the safety regulations have been updated addressing these new scenarios. The mere application of these regulations may lead to a very inefficient behavior of the robot. In order to preserve safety for the human operators and allow the robot to reach a desired configuration in a safe and efficient way, a two layers architecture for trajectory planning and scaling is proposed. The first layer calculates the nominal trajectory and continuously adapts it based on the human behavior. The second layer, which explicitly considers the safety regulations, scales the robot velocity and requests for a new trajectory if the robot speed drops. The proposed architecture is experimentally validated on a Pilz PRBT manipulator.
Highlights
The introduction and diffusion of collaborative robotics within the industrial environments has allowed to create shared workspace where humans and robots can work closely
The ISO 10218-1 and the ISO 10218-2 [2], [3] standards classify the collaborative modes in four different categories: safety-rated monitored stop (SMS), hand guiding (HG), speed and separation monitoring (SSM) and power and force limiting (PFL)
In this paper we propose a novel framework for trajectory planning and velocity scaling for HRC scenario that is aware of the highly dynamic of the environment and ensures safety for the human operator by explicitly considering safety regulations
Summary
The introduction and diffusion of collaborative robotics within the industrial environments has allowed to create shared workspace where humans and robots can work closely. In [12], the authors propose an optimization-based control algorithm that explicitly considers safety in order to avoid the human operator while trying to preserve the desired path Their strategy exploits the use of control barrier functions [13] around the robot body to maintain a collision-free trajectory while fulfilling the ISO/TS 15066. In [14], [15] the authors use kinodynamic rapidly-exploring random tree (RRT) to plan collision free trajectory under kinodynamic constraints These solutions are only suitable for constraints that do not change during the execution of the path, while the safety kinodynamic constraints change in real time based on human behavior. In this paper we propose a novel framework for trajectory planning and velocity scaling for HRC scenario that is aware of the highly dynamic of the environment and ensures safety for the human operator by explicitly considering safety regulations.
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