A simplified hardware-friendly contour prediction algorithm in 3D-HEVC and parallelization design

After the extension of depth modeling mode 4(DMM-4)in 3D high efficiency video coding(3D-HEVC),the computational complexity increases sharply,which causes the real-time performance of video coding to be impacted.To reduce the computational complexity of DMM-4,a simplified hardware-friendly contour prediction algorithm is proposed in this paper.Based on the similarity between texture and depth map,the proposed algorithm directly codes depth blocks to calculate edge regions to reduce the number of reference blocks.Through the verification of the test sequence on HTM16.1,the proposed algorithm coding time is reduced by 9.42%compared with the original algorithm.To avoid the time consuming of serial coding on HTM,a parallelization design of the proposed algorithm based on reconfigurable array processor(DPR-CODEC)is proposed.The parallelization design reduces the storage access time,configuration time and saves the storage cost.Verified with the Xilinx Virtex 6 FPGA,experimental results show that parallelization design is capable of processing HD 1080p at a speed above 30 frames per second.Compared with the related work,the scheme reduces the LUTs by 42.3%,the REG by 85.5%and the hardware resources by 66.7%.The data loading speedup ratio of parallel scheme can reach 3.4539.On average,the different sized templates serial/parallel speedup ratio of encoding time can reach 2.446.

Distributed Model Predictive Contouring Control for Real-Time Multi-Robot Motion Planning

Existing motion planning algorithms for multi-robot systems must be improved to address poor coordination and increase low real-time performance.This paper proposes a new distributed real-time motion planning method for a multi-robot system using Model Predictive Contouring Control(MPCC).MPCC allows separating the tracking accuracy and productivity,to improve productivity better than the traditional Model Predictive Control(MPC)which follows a time-dependent reference.In the proposed distributed MPCC,each robot exchanges the predicted paths of the other robots and generates the collision-free motion in a parallel manner.The proposed distributed MPCC method is tested in industrial operation scenarios in the robot simulation platform Gazebo.The simulation results show that the proposed distributed MPCC method realizes real-time multi-robot motion planning and performs better than three commonly-used planning methods(dynamic window approach,MPC,and prioritized planning).