Design of elastomeric foam-covered robotic manipulators to enhance human safety

Zeng, Lingqi; Bone, Gary M.

doi:10.1016/j.mechmachtheory.2012.09.010

Cited by 10 publications

(12 citation statements)

References 38 publications

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“…This contact location and elbow angle maximizes the moment of inertia of the arm which will produce the maximum impact force, all other parameters being equal. We also assume the impact direction and human's surroundings do not allow the head to move -this is termed a "constrained impact" and produces much larger forces than the unconstrained case where the head is allowed to move [11].…”

Section: Collision Scenariomentioning

confidence: 99%

“…Another method for increasing the safety of an existing robot is to add a compliant cover over its surface, e.g. [7][10] [11]. The cover's stiffness can be chosen to satisfy a safety constraint without being excessively thick [11].…”

Section: Introductionmentioning

confidence: 99%

“…[7][10] [11]. The cover's stiffness can be chosen to satisfy a safety constraint without being excessively thick [11]. The compliant cover cannot be used with the end effector if it interferes with its function.…”

Section: Introductionmentioning

confidence: 99%

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Impact Force Reduction Strategies To Achieve Safer Human-Robot Collisions

Rouzbeh¹,

Bone²

2018

Progress in Canadian Mechanical Engineering

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The increasing use of robots operating close to people has made human-robot collisions more likely. In this paper, strategies intended to reduce the impact force to a safe level, without sacrificing the robot's performance, are investigated. The strategies can be applied to a robot arm without modifying its internal hardware. They include the existing strategies: lowering the actuator controller's stiffness; actuator switched off upon impact detection; withdrawing the arm upon impact detection; and adding a compliant cover. We also propose the novel strategy of limiting the controller's feedback term. The collision scenario studied is a robot arm colliding with a person's constrained head. An improved lumped parameter model of the constrained impact is proposed. Simulation results are included for a UR5 collaborative robot. Sixteen combinations of the impact force reduction strategies are compared. The results show that using a high stiffness controller with a feedback limit and compliant cover reduces the impact force to a safe level, and achieves precise trajectory tracking.

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Section: Collision Scenariomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact Force Reduction Strategies To Achieve Safer Human-Robot Collisions

Rouzbeh¹,

Bone²

2018

Progress in Canadian Mechanical Engineering

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“…So we substitute 0 into (11) and get ( / )[ ( )] + 0 , where ( ) is the gravity term in (1) and is obtained by (18) in our robotic system and 0 is obtained by (9), for ( ) has been able to stabilize the system, so the least squares method can make the parameter 0 meet the following inequality:…”

Section: Definitionmentioning

confidence: 99%

“…In [8,9], a human collaborator in the manipulator's working space was considered and the integration of humans and robots behaviors was discussed. Paper [10] presented a novel control strategy for manipulator in unknown environments.…”

Section: Introductionmentioning

confidence: 99%

Inner-Learning Mechanism Based Control Scheme for Manipulator with Multitasking and Changing Load

Xue

Xiang

2014

Advances in Mechanical Engineering

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With the rapid development of robot technology and its application, manipulators may face complex tasks and dynamic environments in the coming future, which leads to two challenges of control: multitasking and changing load. In this paper, a novel multicontroller strategy is presented to meet such challenges. The presented controller is composed of three parts: subcontrollers, inner-learning mechanism, and switching rules. Each subcontroller is designed with self-learning skills to fit the changing load under a special task. When a new task comes, switching rule reselects the most suitable subcontroller as the working controller to handle current task instead of the older one. Inner-learning mechanism makes the subcontrollers learn from the working controller when load changes so that the switching action causes smaller tracking error than the traditional switch controller. The results of the simulation experiments on two-degree manipulator show the proposed method effect.

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A Position and Torque Switching Control Method for Robot Collision Safety

Yang

et al. 2018

Int. J. Autom. Comput.

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Design of elastomeric foam-covered robotic manipulators to enhance human safety

Cited by 10 publications

References 38 publications

Impact Force Reduction Strategies To Achieve Safer Human-Robot Collisions

Impact Force Reduction Strategies To Achieve Safer Human-Robot Collisions

Inner-Learning Mechanism Based Control Scheme for Manipulator with Multitasking and Changing Load

A Position and Torque Switching Control Method for Robot Collision Safety

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