34 research outputs found
Safe and minimum-time path-following problem for collaborative industrial robots
No full textThanks to their reduced speed and payload, collaborative robotics are, in most of the cases, inherently safe when adopted in relatively simple applications. Other applications, however, still require quick robot movements and/or large payloads, while still taking advantage of sporadic human interventions. In these scenarios, robots are equipped with velocity monitoring capabilities and proximity sensors to reduce their speed as a function of the separating distance with the human worker.
This paper presents a real-time methodology to steer a robotic manipulator along an assigned path in minimum time, while accounting for safety, according to the speed and separation monitoring clause of ISO TS 15066. The methodology has been compared against state-of-the-art research and commercial solutions, showing its outperforming capabilities. The outcome of experiments, which were performed on a COMAU SMART Six industrial robot, are also reported
Towards the Exact Solution for Speed and Separation Monitoring for Improved Human-Robot Collaboration
No full textIn this paper, we approach the problem of ensuring safety requirements within human-robot collaborative scenarios. The safety requirements considered herein are consistent with the paradigm of speed and separation monitoring. In such a setup, safety guarantees for human operators usually imply limited robot velocities and/or significant distance margins, which in turn may have adverse effects regarding the productivity of the robot. In this paper, we propose a novel approach that minimally affects the productivity while being consistent with such a safety prescription. A comprehensive simulation study shows that our method outperforms the current state of the art algorithm
Safe Human-Robot Collaboration via Collision Checking and Explicit Representation of Danger Zones
No full textThis paper deals with safe human-robot collaboration in the context of speed and separation monitoring paradigm. The core of the approach is to continuously track the separation distance between the robot and the human. The robot speed is then adjusted according to the perceived distance so that it will be able to stop before eventually come into contact with the human. We present an approach that aims at maximizing the productivity of the robot, i.e., its speed, while keeping the prescribed safety requirements satisfied. The method is based on explicit representation of danger zones - regions around the robot, where safety requirements are violated. The motion is then generated such that the robot moves as fast as possible, while its danger zone still does not collide with human operators. The approach is validated within an experimental study
Passivity-based control of robotic manipulators for safe cooperation with humans
No full textThis paper presents a novel approach to the control of articulated robots in unstructured environments. The proposed control ensures several properties. First, the controller guarantees the achievement of a goal position without getting stuck in local minima. Then, the controller makes the closed-loop system passive, which renders the approach attractive for applications where the robot needs to safely interact with humans. Finally, the control law is explicitly shaped by the safety measure – the danger field. The proposed control law has been implemented and validated in a realistic experimental scenario, demonstrating the effectiveness in driving the robot to a given configuration in a cluttered environment, without any offline planning phase. Furthermore, the passivity of the system enables the robot to easily accommodate external forces on the tool, when a physical contact between the robot and the environment is established
Combining speed and separation monitoring with power and force limiting for safe collaborative robotics applications
No full textEnabling humans and robots to safely work close to each other deserves careful consideration. With the publication of ISO/TS 15066 directives on this matter, two different strategies, namely the Speed and Separation Monitoring and the Power and Force Limiting, have been proposed. This letter proposes a method to efficiently combine the two aforementioned safety strategies for collaborative robotics operations. By exploiting the combination of the two, it is then possible to achieve higher levels of productivity, while still preserving safety of the human operators. This is achieved by the optimal scaling of the initially prescribed velocity, while preserving the path consistency of the robot trajectory. In a nutshell, the state of motion of each point of the robot is monitored so that at every time instant the robot is able to modulate its speed to eventually come into contact with a body region of the human, consistently with the corresponding biomechanical limit. Validation experiments have been conducted to establish that the proposed method enables substantially less stringent limits on robot performance while still allowing for the safety limits prescribed by ISO directives
Enhanced Performance of Human-Robot Collaboration Using Braking Surfaces and Trajectory Scaling
No full textThis paper presents an effective approach to enable performance improvement in human-robot collaboration scenarios. The problem is tackled from the perspective of speed and separation monitoring principle, which stems from the recently instituted safety standard. The proposed approach attempts to seek for performance gains, measured by the speed-up of the production cycle, without compromising the safety constraints consistent with the standard. The approach is based on the notion of braking surface - an abstraction of the swept volume described by the manipulator during braking motion. We address two types of braking behavior: general and path-consistent. In both cases, the braking surface can be evaluated in a receding horizon manner. The robot velocity is continuously scaled such that, in case of a controlled stop, the corresponding volume spanned by the robot (braking surface) does not interfere with the surrounding obstacles. The approach is entirely kinematic and does not require the knowledge of the robot's dynamic model. Simulation study indicates that the pro-posed approach offers performance improvements compared to other state of the art methods. Moreover, the experiments demonstrate the real-time applicability of the method with the real robot in human-shared environment
Search-based optimal motion planning for automated driving
No full textThis paper presents a framework for fast and robust motion planning designed to facilitate automated driving. The framework allows for real-time computation even for horizons of several hundred meters and thus enabling automated driving in urban conditions. This is achieved through several features. Firstly, a convenient geometrical representation of both the search space and driving constraints enables the use of classical path planning approach. Thus, a wide variety of constraints can be tackled simultaneously (other vehicles, traffic lights, etc.). Secondly, an exact cost-to-go map, obtained by solving a relaxed problem, is then used by A∗-based algorithm with model predictive flavour in order to compute the optimal motion trajectory. The algorithm takes into account both distance and time horizons. The approach is validated within a simulation study with realistic traffic scenarios. We demonstrate the capability of the algorithm to devise plans both in fast and slow driving conditions, even when full stop is required.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Vehicle
