Real-time collision avoidance in human-robot interaction based on kinetostatic safety field

Polverini, Matteo Parigi; Zanchettin, Andrea Maria; Rocco, Paolo

doi:10.1109/iros.2014.6943145

Cited by 39 publications

(22 citation statements)

References 18 publications

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“…The safety field can be interpreted as a set of forces acting on some points along the kinematic chain of a manipulator as illustrated in Figure 2. [6] shows how to compute a configuration q ev induced by the safety field such that the dodging maneuver driving to q ev has a high chance of satisfying the safety constraint, even if this is not guaranteed 100%. By exploiting the properties of the geometrical Jacobian of the manipulator J, [6] defines q ev as follows:…”

Section: B Hybrid Control Strategy For Safe Motion Planningmentioning

confidence: 99%

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Hybrid control of manipulators in human-robot coexistence scenarios

Casalino

Rocco

Prandini

2018

2018 Annual American Control Conference (ACC)

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This paper addresses safe motion planning for a manipulator, in environments shared with human operators. We formulate the problem as an optimal control problem for a hybrid system integrating three different operation modes: nominal, soft safety, and hard safety. The manipulator is assigned a nominal trajectory to reach a target position. If no human is present, then, the manipulator tracks the nominal trajectory; if a human enters its workspace, it tries to avoid it but without adopting too sharp and abrupt actions, except when strictly needed for safety. The decision on when and to what mode to commute is taken online, via a model predictive control approach involving a constrained optimization program with binary variables setting the active/nonactive status of the operating modes. The resulting control input is applied in a receding horizon fashion and the nominal trajectory towards the target is re-computed based on the current state of the system. The proposed approach is applied to a realistic simulation environment and appears computationally feasible and promising.

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Section: B Hybrid Control Strategy For Safe Motion Planningmentioning

confidence: 99%

“…In the soft safety operation mode, the manipulator tries to avoid humans but without adopting too sharp and abrupt actions, which are taken in the hard safety mode but only if needed. We design the hard and soft safety mode controller by integrating the approaches presented in [2], [3], and [6].…”

Section: Introductionmentioning

confidence: 99%

Hybrid control of manipulators in human-robot coexistence scenarios

Casalino

Rocco

Prandini

2018

2018 Annual American Control Conference (ACC)

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“…In cluttered environments, with obstacles, redundancy plays an important role, allowing the robot to reach the goal while avoiding such obstacles. Yet, for achieving real-time path planning capacity for high DOF manipulators in unstructured environments, it is required to merge the redundancy control frameworks with some notion of attraction/repulsion vector fields [4,5]. In such a case, task-level priorities are achieved through projections on the null space of the Jacobian [6], or by using more sophisticated projection criteria [7].…”

Section: Introductionmentioning

confidence: 99%

Collision Avoidance of Redundant Robotic Manipulators Using Newton’s Method

Safeea

Béarée

Neto

2020

J Intell Robot Syst

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This study investigates the application of Newton method to the problems of collision avoidance and path planning for robotic manipulators, especially robots with high Degrees of Freedom (DOF). The proposed algorithm applies to the potential fields method, where the Newton technique is used for performing the optimization. As compared to classical gradient descent method this implementation is mathematically elegant, enhances the performance of motion generation, eliminates oscillations, does not require gains tuning, and gives a faster convergence to the solution. In addition, the paper presents a computationally efficient symbolic formula for calculating the Hessian with respect to joint angles, which is essential for achieving realtime performance of the algorithm in high DOF configuration spaces. The method is validated successfully in simulation environment. Results for different methods (Newton, gradient descent and gradient descent with momentum) are compared in terms of quality of the path generated, oscillations, minimum distance to obstacles and convergence rate.

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“…To prevent severe injuries the safety community developed a wide variety of solutions for example actuation mechanisms [12], [13], collision avoidance control schemes [14], [15] and vision/sensor-based human detection and prediction [16]. However, all these technologies are not yet or only partially allowed for industrial applications.…”

Section: Introductionmentioning

confidence: 99%

End-effector airbags to accelerate human-robot collaboration

Weitschat

Vogel

Lantermann

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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A fundamental problem in human-robot collaboration is to ensure safety for humans being located in the workspace of the robot. Several new robots, referred to as collaborative robots, are pushing into the market. Most of these so-called co-bots have similar properties. They are small, lightweight and designed with big roundings to ensure safety in the case of a collision with a human. Equipped with torque sensors, external torque observers, tactile skins, etc., they are able to stop the robot when an emergency occurs. While developing more and more co-bots, the main focus lies on the robot itself. But to make a robot deployable, a special tool for a defined task is needed. These tools are often sharp-edged and dangerous in case of a collision with a human. In this paper we present a new safety module for robots to ensure safety for different tools in collaborative tasks. This module, filled with air pressure during the robot motion, covers mounted tools and carried workpieces. In case of a non or very slow moving robot, the safety module is able to pull back and the tool is uncovered. In our experiments we found out that we can increase the velocity up to 1 m/s while satisfying the requirements of the ISO/TS 15066 and retain the full functionality of the tool.

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Real-time collision avoidance in human-robot interaction based on kinetostatic safety field

Cited by 39 publications

References 18 publications

Hybrid control of manipulators in human-robot coexistence scenarios

Hybrid control of manipulators in human-robot coexistence scenarios

Collision Avoidance of Redundant Robotic Manipulators Using Newton’s Method

End-effector airbags to accelerate human-robot collaboration

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