Ground Robot Multi-scale Road Perception Based on Semantic Tree MRF Model

doi:10.3969/j.issn.1000-1093.2016.03.017

Abstract

Abstract: Road real-time perception is the key technology of autonomous ground mobile robot to realize autonomous navigation. But it is difficult to develop a road sensing algorithm because of the complexity and uncertainty of outdoor road environment. A multi-scale biomimetic road sensing algorithm in wavelet domain based on semantic tree Markov model is proposed. In time-space domain, the three-dimensional random field is used to express the road image sequence collected by robot. A road model named road best tree-Markov random field (RT-MRF) using the semantic tree structure Markov random field (MRF) is proposed. The genetic algorithm is used to optimize the supervised RT-MRF model for image segmentation of road sequences. The road recognition and autonomous navigation are realized through tracking segmentation boundary. An independently developed quadruped bionic robot is used as the research and experiment platform. The experimental results show that the proposed algorithm is a robust road image sequence segmentation method, which can be used under the poor detection conditions, such as shadow, cracks, holes, uneven and illumination change. And the real time of the algorithm is enough high to meet the demand of outdoor mobile robot autonomous navigation.

Key words: control science and technology, quadruped robot, road detection, multi-scale biomimetic sensing, semantic tree Markov model, wavelet domain

CLC Number:

TP391.41

DU Ming-fang, WANG Jun-zheng, LI Duo-yang, HE Yu-dong. Ground Robot Multi-scale Road Perception Based on Semantic Tree MRF Model[J]. Acta Armamentarii, 2016, 37(3): 512-517.

References

［1］ Semini C，Tsagarakis N G，Guglielmino E，et al. Design of HyQ-a hydraulically and electrically actuated quadruped robot[J]. Proceedings of the Institution of Mechanical Engineers，Part I：Journal of Systems and Control Engineering，2011，225(6)：831-849.
[2］张秀丽. 四足机器人节律运动及环境适应性的生物控制研究[D]. 北京：清华大学，2004.
ZHANG Xiu-li. Biological-inspired rhythmic motion & environmental adaptability for quadruped robot[D].Beijing：Tsinghua University，2004. (in Chinese)
[3］李贻斌，李彬，荣学文，等. 液压驱动四足仿生机器人的结构设计和步态规划[J]. 山东大学学报，2011，41(5)：32-36，45.
LI Yi-bin，LI Bin，RONG Xue-wen，et al. Mechanical design and gait planning of a hydraulically actuated quadruped bionic robot[J]. Journal of Shandong University，2011，41(5)：32-36，45.（in Chinese）
[4］王立鹏,王军政,汪首坤,等.基于足端轨迹规划算法的液压四足机器人步态控制策略[J]. 机械工程学报，2013，49（1）：39-44.
WANG Li-peng, WANG Jun-zheng, WANG Shou-kun, et al. Strategy of foot trajectory generation for hydraulic quadruped robots gait planning[J]. Journal of Mechanical Engineering, 2013，49（1）： 39-44. (in Chinese)
[5］ Crouse M S, Nowak R D, Baraniuk R G. Wavelet-based statistical signal processing using hidden Markov models[J]. IEEE Transactions on Signal Processing, 1998, 46(4): 886-902.
[6］ Choi H，Baraniuk R. Multiscale image segmentation using wavelet-domain hidden Markov models[J]. IEEE Transactions on Image Processing, 2001, 10(9): 1309-1321.
[7］ Li J，Gray R M，Olshen R A. Multiscale image classification by hierarchical modeling with two dimensional hidden Markov models[J]. IEEE Transactions on Information Theory, 2000, 46(5): 1826-1841.
[8］周建军，林春生，赵建扬. 无人飞行器背景磁场学习方法研究[J]. 兵工学报, 2014, 35(1): 76-82.
ZHOU Jian-jun， LIN Chun-sheng，ZHAO Jian-yang. Research on learning flight for unmanned aircraft in background magnetic field[J]. Acta Armamentarii, 2014, 35(1): 76-82. (in Chinese)
[9］伍飞云，周跃海，童峰，等. 可适应稀疏度变化的非均匀范数约束水声信道估计算法[J]. 兵工学报, 2014, 35(9): 1503-1509.
WU Fei-yun, ZHOU Yue-hai, TONG Feng, et al. Non-uniform norm constraint estimation algorithm for underwater acoustic channels at the presence of varying sparsity[J]. Acta Armamentarii, 2014, 35(9): 1503-1509. (in Chinese)
[10］丁良宏. BigDog四足机器人关键技术分析[J]. 机械工程学报, 2015，51(7): 66-87.
DING Liang-hong. Key technology analysis of BigDog quadruped robot[J]. Journal of Mechanical Engineering，2015，51(7): 66- 87. (in Chinese)
[11］张天, 杨晨曦, 朱颖. 多传感器信息融合在四足机器人避障中的应用[J]. 传感器与微系统, 2015(5): 150-153.
ZHANG Tian, YANG Chen-xi, ZHU Ying. Application of multi-sensor information fusion in obstacle avoidance of quadruped robot[J]. Transducer and Microsystem Technologies, 2015(5): 150-153. (in Chinese)
[12］ Zhang T H, Wei Q, Ma H X. Position/force control for a single leg of a quadruped robot in an operation space[J]. International Journal of Advanced Robotic Systems, 2013, 10(137): 1-7.
[13］ Lei J T, Wang F, Yu H Y, et al. Energy efficiency analysis of quadruped robot with trot gait and combined cycloid foot trajectory[J]. Chinese Journal of Mechanical Engineering, 2014, 27(1): 138-145.

[1]	XU Peng, XING Boyang, LIU Yufei, LI Yongyao, ZENG Yi, ZHENG Dongdong. Anti-disturbance Composite Controller Design of Quadruped Robot Based on Extended State Observer and Model Predictive Control Technique [J]. Acta Armamentarii, 2023, 44(S2): 12-21.
[2]	LIU Siyu, LIAO Junbei, LEI Fei, WANG Zhirui, YAN Tong, DANG Ruina, GUO Zhao. Design and Optimization of a Parallel Elastic Actuator Leg for Quadruped Robots [J]. Acta Armamentarii, 2023, 44(S2): 71-83.
[3]	XU Peng, ZHAO Jianxin, FAN Wenhui, QIU Tianqi, JIANG Lei, LIANG Zhenjie, LIU Yufei. Specific Complex Locomotion Skills Control for Quadruped Robots [J]. Acta Armamentarii, 2023, 44(S2): 135-145.
[4]	LI Dian-qi， DUAN Yong. Implementation of Active Disturbance Rejection Control of Robot by Tracking Differentiator [J]. Acta Armamentarii, 2016, 37(9): 1721-1729.
[5]	MENG Ke-zi, ZHOU Di. H_∞ Guidance Law Accounting for Dynamics of Missile Autopilot [J]. Acta Armamentarii, 2016, 37(7): 1194-1202.
[6]	WANG Jie， XIONG Zhi， XING Li， DAI Yi-jie, HUA Bing, LIU Jian-ye. Online Calibration of IMU errors of Inertial Navigation System Based on Innovation-based Adaptive Filtering [J]. Acta Armamentarii, 2016, 37(7): 1203-1213.
[7]	ZHANG Fu-bin, MA Peng, WANG Zhi-hui. SINS/DVL Integrated Navigation Algorithm Based on Transversal Coordinate Frame in Polar Region [J]. Acta Armamentarii, 2016, 37(7): 1229-1235.
[8]	YU Xiao-ting， YU Feng， HE Zhen， XIONG Zhi， WANG Zhen-yu. Virtual Sliding Mode Control-based Attitude Estimation for Non-cooperative Spacecraft [J]. Acta Armamentarii, 2016, 37(7): 1282-1290.
[9]	DUAN Mei-jun, ZHOU Di. A Guidance Law with Finite Time under Control Variable Constraint [J]. Acta Armamentarii, 2016, 37(6): 1030-1037.
[10]	JIN Ying-lian, REN Jie, FENG Wei-bo, LI Jian-jun, WANG Bin-rui. Gait Analysis of an Inchworm-like Robot Climbing on Curved Surface and CPG-based Planning [J]. Acta Armamentarii, 2016, 37(6): 1104-1110.
[11]	CHEN Chen， MA Guang-fu， SUN Yan-chao， LI Chuan-jiang. Recursive Sliding Mode Control for Hypersonic Vehicle Based on Nonlinear Disturbance Observer [J]. Acta Armamentarii, 2016, 37(5): 840-850.
[12]	FENG Ka-li， LI An， QIN Fang-jun， LI Feng. Temperature Error Compensation Method Based on Adaptive Neuro Fuzzy Inference for Fiber-optic Gyro [J]. Acta Armamentarii, 2016, 37(4): 641-647.
[13]	ZHANG Chun-yan, SONG Jian-mei, HOU Bo, ZHANG Min-qiang. Cooperative Guidance Law with Impact Angle and Impact Time Constraints for Networked Missiles [J]. Acta Armamentarii, 2016, 37(3): 431-438.
[14]	DONG Zao-peng， WAN Lei， SUN Yu-shan， LIU Tao， LI Yue-ming， ZHANG Guo-cheng. Trajectory Tracking Control of an Underactuated Unmanned Marine Vehicle Based on Asymmetric Model [J]. Acta Armamentarii, 2016, 37(3): 471-481.
[15]	LIU Ming-yong, ZHU Li, DONG Hai-xia. Research on Gyroscope Array Based on Kalman Filter [J]. Acta Armamentarii, 2016, 37(2): 272-278.