scholarly journals Real-Time Kinematics-Based Self-Collision Avoidance Algorithm for Dual-Arm Robots

2020 ◽  
Vol 10 (17) ◽  
pp. 5893
Author(s):  
Maolin Lei ◽  
Ting Wang ◽  
Chen Yao ◽  
Huan Liu ◽  
Zhi Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Kinematic Model ◽  
Computational Cost ◽  
Time Algorithm ◽  
Upper Body ◽  
Sensitivity Index ◽  
Control Points ◽  
Collision Model ◽  
Dual Arm

Self-collisions of a dual-arm robot system can cause severe damage to the robot. To deal with this problem, this paper presents a real-time algorithm for preventing self-collisions in dual-arm systems. Our first contribution in this work is a novel collision model built using discrete spherical bounding volumes with different radii. In addition, we propose a sensitivity index to measure the distance between spheres with different radii in real time. Next, according to the minimal sensitivity index between different spheres, the repulsive velocity is produced at the centers of the spheres (control points), which the robot uses to generate new motion based on the robot kinematic model. The proposed algorithm offers the additional benefits of a decrease in the number of bounding spheres, and a simple collision model that can effectively decrease the computational cost of the process. To demonstrate the validity of the algorithm, we performed simulations and experiments by an upper-body humanoid robot. Although the repulsive velocity acted on the control points, the results indicate that the algorithm can effectively achieve self-collision avoidance by using a simple collision model.

scholarly journals Application of Artificial Neural Networks in Hybrid Simulation

2019 ◽  
Vol 9 (21) ◽  
pp. 4495 ◽  
Author(s):  
Mucha
Keyword(s):  
Finite Element ◽  
Real Time ◽  
Degrees Of Freedom ◽  
Computational Cost ◽  
Hybrid Simulation ◽  
Time Algorithm ◽  
High Accuracy ◽  
Small Time ◽  
Fe Model ◽  
Artificial Neural

Hybrid simulation is a technique for testing mechanical systems. It applies to structures with elements hard or impossible to model numerically. These elements are tested experimentally by straining them by means of actuators, while the rest of the system is simulated numerically using a finite element method (FEM). Data is interchanged between experiment and simulation. The simulation is performed in real-time in order to accurately recreate the dynamic behavior in the experiment. FEM is very computationally demanding, and for systems with a great number of degrees of freedom (DOFs), real-time simulation with small-time steps (ensuring high accuracy) may require powerful computing hardware or may even be impossible. The author proposed to swap the finite element (FE) model with an artificial neural network (ANN) to significantly lower the computational cost of the real-time algorithm. The presented examples proved that the computational cost could be reduced by at least one number of magnitude while maintaining high accuracy of the simulation; however, obtaining appropriate ANN was not trivial and might require many attempts.

A real-time dual-arm collision avoidance algorithm for assembly

2001 ◽  
Vol 18 (8) ◽  
pp. 477-486 ◽  
Author(s):  
Sukhan Lee ◽  
Hadi Moradi
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Dual Arm

scholarly journals Real-Time Collision-Free Navigation of Multiple UAVs Based on Bounding Boxes

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1632
Author(s):  
Paloma Sánchez ◽  
Rafael Casado ◽  
Aurelio Bermúdez
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Computational Cost ◽  
Multiple Uavs ◽  
Navigation Algorithms ◽  
Excellent Candidate ◽  
Bounding Boxes ◽  
Velocity Obstacle ◽  
High Computational Cost ◽  
Multi Uav

Predictably, future urban airspaces will be crowded with autonomous unmanned aerial vehicles (UAVs) offering different services to the population. One of the main challenges in this new scenario is the design of collision-free navigation algorithms to avoid conflicts between flying UAVs. The most appropriate collision avoidance strategies for this scenario are non-centralized ones that are dynamically executed (in real time). Existing collision avoidance methods usually entail a high computational cost. In this work, we present Bounding Box Collision Avoidance (BBCA) algorithm, a simplified velocity obstacle-based technique that achieves a balance between efficiency and cost. The performance of the proposal is analyzed in detail in different airspace configurations. Simulation results show that the method is able to avoid all the conflicts in two UAV scenarios and most of them in multi-UAV ones. At the same time, we have found that the penalty of using the BBCA collision avoidance technique on the flying time and the distance covered by the UAVs involved in the conflict is reasonably acceptable. Therefore, we consider that BBCA may be an excellent candidate for the design of collision-free navigation algorithms for UAVs.

scholarly journals A Real-Time Upper-Body Robot Imitation System

2019 ◽  
Vol 2 (1) ◽  
pp. 49 ◽  
Author(s):  
Zhijun Zhang ◽  
Yaru Niu ◽  
Lingdong Kong ◽  
Shuyang Lin ◽  
Hao Wang
Keyword(s):  
Real Time ◽  
Humanoid Robot ◽  
Computational Cost ◽  
Human Head ◽  
Inverse Kinematic ◽  
Recognition Algorithm ◽  
Upper Body ◽  
State Recognition ◽  
Hand Motion ◽  
Arm Motions

An upper-body robot imitation (UBRI) system is proposed and developed to enable the human upper body imitation by a humanoid robot in real time. To achieve the imitation of arm motions, a geometry-based analytical method is presented and applied to extracting the joint angles of the human and mapping to the robot. Comparing to the traditional numerical methods of inverse kinematic computations, the geometrical analysis method generates a lower computational cost and maintains good imitation similarity. To map the human head motions to the head of the humanoid robot, a face tracking algorithm is employed to recognize the human face and track the human head poses in real time. A hand extraction and hand state recognition algorithm is proposed to achieve the hand motion mapping. At last, the completion rate and similarity evaluation experiments are conducted to verify the effectiveness of the proposed UBRI system.

scholarly journals Avatar Locomotion in Crowd Simulation

2011 ◽  
Vol 10 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Nuria Pelechano ◽  
Bernhard Spanlang ◽  
Alejandro Beacco
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Crowd Simulation ◽  
Character Animation ◽  
Upper Body ◽  
Virtual Characters ◽  
Continuous Space ◽  
Visual Results

This paper presents an Animation Planning Mediator (APM) designed to synthesize animations efficiently for virtual characters in real time crowd simulation. From a set of animation clips, the APM selects the most appropriate and modifies the skeletal configuration of each character to satisfy desired constraints (e.g. eliminating foot-sliding or restricting upper body torsion), while still providing natural looking animations. We use a hardware accelerated character animation library to blend animations increasing the number of possible locomotion types. The APM allows the crowd simulation module to maintain control of path planning, collision avoidance and response. A key advantage of our approach is that the APM can be integrated with any crowd simulator working in continuous space. We show visual results achieved in real time for several hundreds of agents, as well as the quantitative ac-curacy.

Sky Segmentation for Enhanced Depth Reconstruction and Bokeh Rendering with Efficient Architectures

2020 ◽  
Vol 2020 (14) ◽  
pp. 378-1-378-7
Author(s):  
Tyler Nuanes ◽  
Matt Elsey ◽  
Radek Grzeszczuk ◽  
John Paul Shen
Keyword(s):  
Real Time ◽  
Mobile Device ◽  
Computational Cost ◽  
False Positives ◽  
Compact Model ◽  
High Quality ◽  
False Negatives ◽  
Trade Off ◽  
Depth Reconstruction ◽  
Binary Classifiers

We present a high-quality sky segmentation model for depth refinement and investigate residual architecture performance to inform optimally shrinking the network. We describe a model that runs in near real-time on mobile device, present a new, highquality dataset, and detail a unique weighing to trade off false positives and false negatives in binary classifiers. We show how the optimizations improve bokeh rendering by correcting stereo depth misprediction in sky regions. We detail techniques used to preserve edges, reject false positives, and ensure generalization to the diversity of sky scenes. Finally, we present a compact model and compare performance of four popular residual architectures (ShuffleNet, MobileNetV2, Resnet-101, and Resnet-34-like) at constant computational cost.

Longitudinal and lateral collision avoidance control strategy for intelligent vehicles

2021 ◽  
pp. 095440702110240
Author(s):  
Ziyu Zhang ◽  
Chunyan Wang ◽  
Wanzhong Zhao ◽  
Jian Feng
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Decentralized Control ◽  
Control Strategy ◽  
Centralized Control ◽  
Lateral Control ◽  
Time Performance ◽  
Collision Avoidance Control ◽  
Avoidance Control ◽  
Control Accuracy

In order to solve the problems of longitudinal and lateral control coupling, low accuracy and poor real-time of existing control strategy in the process of active collision avoidance, a longitudinal and lateral collision avoidance control strategy of intelligent vehicle based on model predictive control is proposed in this paper. Firstly, the vehicle nonlinear coupling dynamics model is established. Secondly, considering the accuracy and real-time requirements of intelligent vehicle motion control in pedestrian crossing scene, and combining the advantages of centralized control and decentralized control, an integrated unidirectional decoupling compensation motion control strategy is proposed. The proposed strategy uses two pairs of unidirectional decoupling compensation controllers to realize the mutual integration and decoupling in both longitudinal and lateral directions. Compared with centralized control, it simplifies the design of controller, retains the advantages of centralized control, and improves the real-time performance of control. Compared with the decentralized control, it considers the influence of longitudinal and lateral control, retains the advantages of decentralized control, and improves the control accuracy. Finally, the proposed control strategy is simulated and analyzed in six working conditions, and compared with the existing control strategy. The results show that the proposed control strategy is obviously better than the existing control strategy in terms of control accuracy and real-time performance, and can effectively improve vehicle safety and stability.

Sign in / Sign up

Export Citation Format

Share Document