Young Loul Kim

Collision Detection Algorithm to Distinguish Between Intended Contact and Unexpected Collision

Abstract Industrial and service robots often physically interact with humans, and thus, human safety during these interactions becomes significantly important. Several solutions have been proposed to guarantee human safety, and one of the most practical, efficient solutions is the collision detection using generalized momentum and joint torque sensors. This method allows a robot to detect a collision and react to it as soon as possible to minimize the impact. However, the conventional collision detection methods cannot distinguish between intended contacts and unexpected collisions, and thus they cannot be used during certain tasks such as teaching and playback or force control. In this paper, we propose a novel collision detection algorithm which can distinguish intended contacts and unexpected collisions. In most cases, the external force during a collision shows a noticeably faster rate of change than that during an intended contact, and using this difference, the proposed observer can distinguish one from the other. Several experiments were conducted to show that the proposed algorithm can effectively distinguish intended contacts and unexpected collisions.

Automated guidance of peg-in-hole assembly tasks for complex-shaped parts

To prevent the failure of peg-in-hole assembly tasks involving geometrically complex parts, a force control-based assembly strategy that takes geometric information into account is required. Therefore, in this study, we propose an assembly strategy for complex-shaped parts which performs force control based on visually-obtained geometric information and CAD models. CAD models are used to obtain geometric information about the parts, and a camera is used to track their position and orientation. In addition, an impedance control scheme is used to control the contact force to avoid excessive force during assembly tasks. The performance of the proposed guidance algorithm was evaluated by a series of experiments using arbitrary complex-shaped parts.

Novel collision detection index based on joint torque sensors for a redundant manipulator

Human-robot collision has drawn increasing attention in recent years and collision safety can be improved by successfully detecting collisions between a human and a robot. For a manipulator working in human environments, collisions usually occur at the manipulator body while the robot performs a contact task using its end-effector to interact with the environment. Therefore, both collision force and the force on the end-effector contribute to the external torques which can be estimated from the robot dynamics and the joint torques measured by the joint torque sensors, which means whether or not a collision has occurred cannot be reliably determined using this estimation. In this study, we propose a novel collision detection index to detect collisions independently of the end-effector force of a redundant manipulator equipped with joint torque sensors. Using the null space projection of a redundant manipulator, the collision detection index can be expressed as a function of the torque generated by a collision and the manipulator configuration. The proposed index is verified through various simulations. Simulation results show that collisions can be reliably detected regardless of the presence of the end-effector forces even in situations with external torques contaminated by substantial error.

Preliminary experiments on robotic assembly using a hybrid-type variable stiffness actuator

Precision robotic assembly requires compliant motion to avoid jamming or wedging. To achieve compliant motion, impedance control and a passive compliance device, such as a RCC (remote center compliance) device, have been used in robotic assembly. However, impedance control cannot provide low impedance for the high-frequency range, and load capacity and allowable misalignment of the RCC device are limited. To cope with these problems, we propose to use a variable stiffness actuator in robotic assembly. The 3-DOF manipulator including two HVSAs was developed, and the experiments on robotic assembly were carried out. Two HVSAs provide low impedance to compensate for the lateral and angular errors between the assembly parts. To show the advantages of the HVSA-actuated manipulator over the force-controlled manipulator, we conducted comparison experiments on robotic assembly with the 6-DOF robot manipulator which was controlled by an impedance controller. A series of experiments show that the HVSA-actuated manipulator is more beneficial to execute the tasks requiring both fast motion for high efficiency and low impedance for operational safety.

Impedance-Control Based Peg-in-Hole Assembly with a 6 DOF Manipulator

The maximum accuracy of position control by using an industrial robot is about , whereas the maximum tolerated imprecision in the position of precision parts is about several tens of micrometers. Therefore, it is very difficult to assemble parts by position control only. Moreover, in the case of precision assembly, jamming or wedging can easily occur because of small position/orientation errors, which may damage the parts to be assembled. To overcome these problems, we investigated a force control scheme that provides proper motion in response to the contact force. In this study, we constructed a force control system that can be easily implemented in a position-controlled manipulator. Impedance control by using an admittance filter was adopted to perform stable contact tasks. It is shown that the precision parts can be assembled well by adopting impedance control and blind search methods.

A Switching Notch Filter for Reducing the Torque Ripple Caused by a Harmonic Drive in a Joint Torque Sensor

Harmonic drives have been widely used in combination with joint torque sensors in order to facilitate accurate manipulator control. A harmonic drive causes a torque ripple because of its structural characteristics, and this torque ripple tends to deteriorate the performance of a controller or observer that uses torque sensors. This paper proposes a switching notch filter for reducing the torque ripple caused by a harmonic drive in a joint torque sensor; the functioning of this filter is based on the relationship between the frequency components of the torque ripple and the rotational velocity of the harmonic drive. The proposed switching notch filter is advantageous in that it requires less computational load and does not necessitate additional circuits or structures. Various experiments demonstrate that the proposed filter has good filtering performance, fast response, and good switching stability.

Hole detection algorithm for square peg-in-hole using force-based shape recognition

It is very difficult to assemble precision parts using only position control. To deal with these problems, force control approaches, which provide a proper motion response against the contact force, were investigated. Moreover, hole detection is a crucial step to eliminate the uncertainty in robotic assembly. Without a proper hole detection algorithm, assembly time increases along with the position difference between the peg and the hole. In this study, we propose a shape recognition algorithm based on a 6 axis F/T sensor and the hole detection algorithm. The proposed hole detection algorithm can find the direction of the hole regardless of the size of the position error between a peg and a hole. The same algorithm can be implemented not only to a circular peg, but also to a polygonal convex peg. A series of experimental results show that the proposed algorithms can estimate the shape and location of a peg reasonably well.

Guidance algorithm for complex-shape peg-in-hole strategy based on geometrical information and force control

Abstract This paper suggests a solution for peg-in-hole problems involving complex geometry. Successful completion of peg-in-hole assembly tasks depends on a geometry-based approach for determining the guiding direction, fine contact motion control, and a reference force for the alignment/insertion process as well. Therefore, in this study, we propose a peg-in-hole strategy for complex-shaped parts based on a guidance algorithm. This guidance algorithm is inspired by the study of human motion patterns; that is, the assembly direction selection process and the maximum force threshold are determined through the observation of humans performing similar actions. In order to carry out assembly tasks, an assembly direction is chosen using the spatial arrangement and geometric information of complex-shaped parts, and the required force is decided by kinesthetic teaching with a Gaussian mixture model. In addition, an impedance controller using an admittance filter is implemented to achieve stable contact motion for a position control-based industrial robot. The performance of the proposed assembly strategy was evaluated by experiments using arbitrarily complex-shaped parts with different initial situations.

Adaptation-and-collision detection scheme for safe physical human-robot interaction

Human-robot collisions are unavoidable during a human-robot interaction. Thus, a number of collision detection algorithms have been proposed to ensure human safety during such an occasion. However, collision detection algorithms are usually model-based, requiring an accurate model of the robot. The errors in the model can lead to the malfunction of the algorithms. In this study, we propose an adaptation and collision detection scheme to improve the sensitivity of the collision detection algorithm. Performing adaptation prior to collision detection will effectively minimize the model uncertainty of the robot. This minimization will allow sensitive, reliable collision detection. By using torque filtering, adaptation and collision detection can be done without the need for the acceleration estimation. The performance of the proposed scheme is demonstrated by various experiments.

Direct teaching algorithm based on task assistance for machine tending

Much research has been done on direct teaching in which an operator directly teaches a robot its task by hand guiding. In this study, we propose a novel algorithm to add virtual stiffness to a robot based on its task without changing the mode of teaching. The proposed algorithm defines the task assistance domains with spherical, cylindrical, and hexahedral shapes depending on the task environment. Inside this domain, stiffness is added to assist the operator in teaching the robot. At the boundary of the task assistance domain, stiffness is gradually changed to avoid the instability due to an abrupt change in stiffness. The proposed method was implemented on a 6 DOF industrial robot performing direct teaching for machine tending to demonstrate its feasibility. The experiments show that the operator can perform direct teaching more efficiently and this algorithm is particularly good for repetitive teaching on a small batch production.