Disturbance observer based force control of robot manipulator without force sensor

Eom, K.S.; Suh, Il Hong; Chung, Wan Kyun; Oh, Sang–Rok

doi:10.1109/robot.1998.680888

Cited by 123 publications

(77 citation statements)

References 9 publications

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“…In rigid link robots contact forces/torques at the endeffector are estimated using joint forces/torques [20] [21]. The continuum manipulator is modeled as a rigid link robot with revolute joints [22].…”

Section: Rigid Link Modelmentioning

confidence: 99%

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Force sensing in continuum manipulators using fiber Bragg grating sensors

Khan

Roesthuis

Misra

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-The presence of force feedback in medical instruments has been proven to reduce tissue damage. In order to provide force feedback, information about the interaction forces between the instrument and the environment must be known. Direct measurement of these forces by commercial sensors is not feasible due to space limitations. Thus, in this study we propose to estimate the interaction forces using strain measurements from Fiber Bragg Grating (FBG) sensors. These measurements can also be used for shape sensing and as a result both force and shape can be sensed simultaneously. For force sensing two models are proposed and compared. The first is based on a Rigid Link approximation, while the second uses the Cosserat rod theory. The models are validated experimentally using a tendon-driven continuum manipulator that is subjected to forces at the tip. The force estimates from the models are compared to the measurements from a commercial force sensor. Mean absolute errors of 11.2 mN (6.9%) and 15.9 mN (8.3%) are observed for the Rigid Link model and Cosserat model, respectively.

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Section: Rigid Link Modelmentioning

confidence: 99%

“…The rotation matrix R(s) in (20) is calculated from (16). Thus, (20) gives the external force based on any point on the arc length and the evaluated parameters on the right hand side of the equation.…”

Section: B Contact Force Estimationmentioning

confidence: 99%

Force sensing in continuum manipulators using fiber Bragg grating sensors

Khan

Roesthuis

Misra

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…The top diagram shows the measured force magnitude from the wrist-mounted force/torque sensor, and the bottom plot shows the torque magnitude. The experiment was performed three times; first with no friction compensation, then with friction compensation based on velocity only according to (5), and finally with the full friction compensation.…”

Section: B the Use Of Large Integral Gainmentioning

confidence: 99%

“…7, which shows the force and torque magnitude from the wrist-mounted force/torque sensor. The experiment was performed three times; first with no friction compensation, then with friction compensation based on the measured velocity, i.e., according to (5), and finally with the full friction compensation, where also the method with large integral gain was used. Without friction compensation, the largest applied force and torque was needed, as can be seen in the diagrams.…”

Section: Lead-through Programming Performancementioning

confidence: 99%

“…One standard approach for performing sensorless force control has been based on using dynamical models of the robot together with the measured joint positions, where the applied force can be estimated with disturbance observers [5], [6]. Another approach is based on using the motor torques to estimate the applied external torques; two such examples are [7], [8].…”

Section: Introductionmentioning

confidence: 99%

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Sensorless friction-compensated passive lead-through programming for industrial robots

Stolt

Carlson

Ardakani

et al. 2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Industrial robots are important when the degree of automation in industry is increased. To enable the use of robots also when the products change rapidly, the programming must be quick and easy to perform. One way to accomplish this is to use lead-through programming, i.e., the user manually guides the robot. This paper presents a sensorless approach, and thus avoids the need for a typically expensive sensor. The method is based on disabling low-level joint controllers combined with gravity compensation. It is reported how the performance can be improved by compensating for friction. Further, a method for detecting small external torques is described, based on the use of the low-level joint controllers with increased integral gain. The lead-through programming is experimentally evaluated using two different industrial robots.

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