Instantaneous stiffness effects on impact forces in human-friendly robots

Shin, Dong-Chun; Quek, Zhan Fan; Phan, Samson; Cutkosky, Mark R.; Khatib, Oussama

doi:10.1109/iros.2011.6094675

Cited by 5 publications

(9 citation statements)

References 13 publications

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“…As reported in [13], dynamic stiffness diminishes as impact frequency increases. Figure 3a shows that the dynamic joint stiffness is proportional to k m initially, then quickly decreases to zero as a force controllers compensate for force error.…”

Section: Identification Of Dynamic Stiffnesssupporting

confidence: 60%

“…However, the stiffness approaches k m at a high frequency due to the control bandwidth limitation. Figure 3d shows that a higher controller gain further decreases the stiffness at a low frequency, while at a high frequency the stiffness eventually converges to k m independent of controller gain [13].…”

Section: Identification Of Dynamic Stiffnessmentioning

confidence: 97%

“…In order to properly evaluate stiffness effects on robot performance along with robot safety, Shin developed an effective dynamic stiffness model combining an inherent stiffness generated by PAMs and active stiffness produced by a controller in the frequency domain [13]. Our stiffness model further characterizes how a joint behaves when an actuator and/or a controller affect dynamic joint stiffness.…”

Section: Dynamic Stiffness Modelmentioning

confidence: 99%

“…E is PAM property including k valve , which is empirically obtained valve gain. b and n are muscle constants [14] (see [13] for the detailed equations). From Eq.…”

Section: Dynamic Stiffness Modelmentioning

confidence: 99%

“…3b [13]. Figures 3c-d show the effective dynamic stiffness in the frequency domain [13]. At a low frequency, the stiffness converges to zero due to the joint torque control.…”

Section: Identification Of Dynamic Stiffnessmentioning

confidence: 99%

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Effective Dynamic Stiffness Model and Its Effects on Robot Safety and Performance

Shin

Quek

2013

Transactions of the Canadian Society for Mechanical Engineering

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Due to the limited control bandwidth of pneumatic artificial muscles, joint stiffness characteristics and their effects on safety and performance of human-friendly robots should be considered in the frequency domain. This paper introduces the concept of effective dynamic stiffness and validates its model with the Stanford Safety Robot. Experimental results show that the dynamic stiffness demonstrates limited effects on the impact acceleration given the same impact velocity and controller gain, whereas it significantly affects control performance of position tracking due to pressure-induced non-linearities. A stiffness optimization strategy for safety and performance is discussed as a design guideline of human-friendly robots.

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Section: Identification Of Dynamic Stiffnesssupporting

confidence: 60%

Section: Identification Of Dynamic Stiffnessmentioning

confidence: 97%

Section: Dynamic Stiffness Modelmentioning

confidence: 99%

“…E is PAM property including k valve , which is empirically obtained valve gain. b and n are muscle constants [14] (see [13] for the detailed equations). From Eq.…”

Section: Dynamic Stiffness Modelmentioning

confidence: 99%

“…3b [13]. Figures 3c-d show the effective dynamic stiffness in the frequency domain [13]. At a low frequency, the stiffness converges to zero due to the joint torque control.…”

Section: Identification Of Dynamic Stiffnessmentioning

confidence: 99%

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Effective Dynamic Stiffness Model and Its Effects on Robot Safety and Performance

Shin

Quek

2013

Transactions of the Canadian Society for Mechanical Engineering

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Model predictive control for fast reaching in clutter

2015

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A key challenge for haptically reaching in dense clutter is the frequent contact that can occur between the robot's arm and the environment. We have previously used single-time-step model predictive control (MPC) to enable a robot to slowly reach into dense clutter using a quasistatic mechanical model. Rapid reaching in clutter would be desirable, but entails additional challenges due to dynamic phenomena that can lead to higher forces from impacts and other types of contact. In this paper, we present a multi-timestep MPC formulation that enables a robot to rapidly reach a target position in dense clutter, while regulating wholebody contact forces to be below a given threshold. Our controller models the dynamics of the arm in contact with the environment in order to predict how contact forces will change and how the robot's end effector will move. It also models how joint velocities will influence potential impact forces. At each time step, our controller uses linear models to generate a convex optimization problem that it can solve efficiently. Through tens of thousands of trials in simulation, we show that with our dynamic MPC a simulated robot can, on average, reach goals 1.4 to 2 times faster than our previous controller, while attaining comparable success rates and fewer occurrences of high forces. We also conducted trials using a real 7 degree-of-freedom (DoF) humanoid robot arm with whole-arm tactile sensing. Our controller enabled Electronic supplementary material The online version of this article (

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Fast reaching in clutter while regulating forces using model predictive control

Killpack

Kemp

2013

2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids)

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Moving a robot arm quickly in cluttered and unmodeled workspaces can be difficult because of the inherent risk of high impact forces. Additionally, compliance by itself is not enough to limit contact forces due to multi-contact phenomena (jamming, etc.). The work in this paper extends our previous research on manipulation in cluttered environments by explicitly modeling robot arm dynamics and using model predictive control (MPC) with whole-arm tactile sensing to improve the speed and force control. We first derive discretetime dynamic equations of motion that we use for MPC. Then we formulate a multi-time step model predictive controller that uses this dynamic model. These changes allow us to control contact forces while increasing overall end effector speed. We also describe a constraint that regulates joint velocities in order to mitigate unexpected impact forces while reaching to a goal. We present results using tests from a simulated three link planar arm that is representative of the kinematics and mass of an average male's torso, shoulder and elbow joints reaching in high and low clutter scenarios. These results show that our controller allows the arm to reach a goal up to twice as fast as our previous work, while still controlling the contact forces to be near a user-defined threshold.

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Instantaneous stiffness effects on impact forces in human-friendly robots

Cited by 5 publications

References 13 publications

Effective Dynamic Stiffness Model and Its Effects on Robot Safety and Performance

Effective Dynamic Stiffness Model and Its Effects on Robot Safety and Performance

Model predictive control for fast reaching in clutter

Fast reaching in clutter while regulating forces using model predictive control

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