针对RRT-Connect算法在复杂环境下路径规划效率低、避障能力差以及生成路径质量差等问题，提出一种改进的RRT-Connect算法。首先，提出一种双向目标偏向策略，增加算法的目标导向性以及路径规划效率。其次，提出一种避障优化策略，增加算法在复杂环境下的主动避障能力以及通过能力。最后，加入路径重组策略和平滑策略对生成的初始路径进行优化处理，减少路径长度及拐点，提高路径质量。通过MATLAB将改进算法与其他算法在3种复杂环境下进行对比研究。仿真结果表明，改进算法相对规划时间更少、路径长度更短、采样次数更少、路径规划成功率更高，证明了改进算法在复杂环境下的有效性。

To address the issues of low path planning efficiency, poor obstacle avoidance capability, and low path quality of the RRT-Connect algorithm in complex environments, an improved RRT-Connect algorithm was proposed. Firstly, a bidirectional goal bias strategy was introduced to enhance the goal-directedness and path planning efficiency of the algorithm. Secondly, an obstacle avoidance optimization strategy was proposed to increase the algorithm's active obstacle avoidance capability and passage ability in complex environments. Finally, a path recombination strategy and a smoothing strategy were added to optimize the generated initial path, reducing path length and the number of turns, and improving path quality. The improved algorithm was compared with other algorithms in three complex environments using MATLAB. Simulation results show that the improved algorithm has less planning time, shorter path length, fewer sampling times, and a higher success rate of path planning, demonstrating the effectiveness of the improved algorithm in complex environments.