This paper studied the collision detection of robot manipulators for safe collaboration in human-robot interaction. Based on sensor-based collision detection, external torque is detached from subtracting robot dynamics. To detect collision using joint torque sensor data, a comparative study was conducted using data-based machine learning algorithm. Data was collected from the actual 3 degree-of-freedom (DOF) robot manipulator, and the data was labeled by threshold and handwork. Using support vector machine (SVM), decision tree and k-nearest neighbors KNN method, we derive the optimal parameters of each algorithm and compare the collision classification performance. The simulation results are analyzed for each method, and we confirmed that by an optimal collision status detection model with high prediction accuracy.

This paper deals with the development and application of control algorithms for series elastic relief robots for rescue operations in harsh environment like disasters or battlefield. The joint controller applied in this paper has a cascade structure combining inner loop for torque control and outer loop for position control. The torque loop contains feedforward and feedback controller and disturbance observer for independent, decentralized joint control. The effect of the elastic component and motor dynamics are treated as the nonlinear disturbance and compensated with the disturbance observer of torque controller. For the collision detection, Band Designed Disturbance Observer is configured to recognize/respond to external disturbance robustly in the continuously changing environment. The controller is applied to a 7-dof series elastic manipulator to evaluate the torque tracking and collision detection/response performance.

In this paper, we propose a new collision detection algorithm for human-robot collaboration. We use an IMU sensor located at the tip of the manipulator and the kinematic behavior of the manipulator to detect the unexpected collision between the robotic manipulator and environment. Unlike other method, the developed algorithm uses only the kinematic relationship between the manipulator joint and the end effector. Therefore, the collision estimation signal is not affected by the error of the dynamics model. The proposed collision detection algorithm detects the collision by comparing the estimated acceleration of the end effector derived from the position, velocity and acceleration trajectories of the robot joints with the actual acceleration measured by the sensor. In simulation, we compare the performance of our method with the conventional Residual Observer (ROB). Our method is less sensitive to the load variation because of the independency on the dynamic modeling of the manipulator.

Human-robot co-operation becomes increasingly frequent due to the widespread use of service robots. However, during such co-operation, robots have a high chance of colliding with humans, which may result in serious injury. Thus, many solutions were proposed to ensure collision safety, and among them, collision detection algorithms are regarded as one of the most practical solutions. They allow a robot to quickly detect a collision so that the robot can perform a proper reaction to minimize the impact. However, conventional collision detection algorithms required the precise model of a robot, which is difficult to obtain and is subjected to change. Also, expensive sensors, such as torque sensors, are often required. In this study, we propose a novel collision detection algorithm which only requires motor encoders. It detects collisions by monitoring the high-pass filtered version of the velocity error. The proposed algorithm can be easily implemented to any robots, and its performance was verified through various tests.

Collision is a brief dynamic event consisting of the close approach of two or more objects or particles resulting in an abrupt change of momentum or exchange of energy because of interaction. Collisions play very important role in computer graphics, computer games and animations fields. Collisions can supply active interaction between cyberspace and real world and give much interests for making nice games so reasonable collision detection algorithms are needed. Collision detection algorithms should satisfy being fast and accuracy. In this paper, we survey the 2D collision detection algorithms between geometric models. We present several methods and system available for collision detection.