Collision Detection and Safe Reaction with the DLR-III Lightweight Manipulator Arm

Luca, Alessandro De; Albu‐Schäffer, Alin; Haddadin, Sami; Hirzinger, Gerd

doi:10.1109/iros.2006.282053

Cited by 590 publications

(471 citation statements)

References 23 publications

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“…In order not to damage its environment and in particular the objects it is supposed to manipulate, the robot should be able to quickly detect collisions and safely react to them. The collision detection method we use was introduced and evaluated in [De Luca et al, 2006], [Haddadin et al, 2008]. It provides not only binary contact information but also an accurate estimation of the external torques.…”

Section: Impedance Control and Collision Detection For Sensitive Grasmentioning

confidence: 99%

Rigid 3D geometry matching for grasping of known objects in cluttered scenes

Papazov

Haddadin

Parusel

et al. 2012

The International Journal of Robotics Research

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145

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Abstract-In this paper, we present an efficient 3D object recognition and pose estimation approach for grasping procedures in cluttered and occluded environments. In contrast to common appearance-based approaches, we rely solely on 3D geometry information. Our method is based on a robust geometric descriptor, a hashing technique and an efficient, localized RANSAC-like sampling strategy. We assume that each object is represented by a model consisting of a set of points with corresponding surface normals. Our method simultaneously recognizes multiple model instances and estimates their pose in the scene. A variety of tests shows that the proposed method performs well on noisy, cluttered and unsegmented range scans in which only small parts of the objects are visible. The main procedure of the algorithm has a linear time complexity resulting in a high recognition speed which allows a direct integration of the method into a continuous manipulation task. The experimental validation with a 7-degrees-of-freedom Cartesian impedance controlled robot shows how the method can be used for grasping objects from a complex random stack. This application demonstrates how the integration of computer vision and softrobotics leads to a robotic system capable of acting in unstructured and occluded environments.

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Section: Impedance Control and Collision Detection For Sensitive Grasmentioning

confidence: 99%

Rigid 3D geometry matching for grasping of known objects in cluttered scenes

Papazov

Haddadin

Parusel

et al. 2012

The International Journal of Robotics Research

Self Cite

145

View full text Add to dashboard Cite

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“…There are also other detection collision/interaction techniques without using external sensors, such as in De Luca and colleagues. 13,14 The sensorless collision detection is the latest research direction. This technique does not use any extra sensors, such as torque sensors or accelerometers, and it is proposed in this research.…”

Section: Introductionmentioning

confidence: 99%

A universal algorithm for sensorless collision detection of robot actuator faults

Chen

Luo

2018

Advances in Mechanical Engineering

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When a robot is working properly, it is possible to collide with people or objects entering its working space. This research is different than usual control algorithm. It proposes a universal algorithm for sensorless collision detection of robot actuator faults to enhance the security of the robot. On the basis of the dynamic model, a classical friction model to ensure the accuracy of the whole dynamic model is introduced. This collision detection algorithm can conduct without any external sensors or acceleration and realize the real-time detection just needs to measure the motor current and the location information from the encoder of the robot joint. The value of external torque t ext was used to compare with the threshold to detect the collision. After using the proposed collision detection method, the two rotational (2R) planar manipulators can detect the slight collision reliably. The experimental results and performance comparisons show that this sensorless collision detection algorithm is simple and effective. It can be promoted to any other type of robot arm with more degrees of freedom.

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“…Another approach is based on using the motor torques to estimate the applied external torques; two such examples are [7], [8]. An approach for detection of external torques without external sensing using the generalized momentum is [9], where the method relies on knowledge of a dynamical model of the robot. A method to decrease the low velocity friction uncertainties using dithering when doing force estimation was presented in [10].…”

Section: Introductionmentioning

confidence: 99%

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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Collision Detection and Safe Reaction with the DLR-III Lightweight Manipulator Arm

Cited by 590 publications

References 23 publications

Rigid 3D geometry matching for grasping of known objects in cluttered scenes

Rigid 3D geometry matching for grasping of known objects in cluttered scenes

A universal algorithm for sensorless collision detection of robot actuator faults

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

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