A robotic arm obstacle avoiding path planning method is provided. The method includes the following steps: step 1: simplifying the robotic arm model and obstacles, determining robotic arm joint points, and adopting virtual joint interpolation to interpolate connecting rods between adjacent joints; employing spherical bounding boxes at each joint point to envelop and replace the robotic arm model, enabling complete substitution for distance calculation when the robotic arm assumes any posture; step 2: adopting an eye-to-hand configuration to position the depth camera, acquiring in real time the point cloud information of the robotic arm and obstacles in the workspace, and using a robot real-time filtering package to filter out the point cloud information of the robotic arm itself.

Disclosed techniques for graph generation for online path planning offer multiple advantages, such as providing for high-quality motion during online operation of the robot, while reducing the computational burden of graph generation. Achieving these competing goals involves reducing the dimensionality of the graph generation problem by performing unconstrained sampling that defines partial robot poses that set values for fewer than all configuration parameters of the robot. The remaining configuration parameters for each sample are then determined in dependence on a distance function that relates the partial pose to one or more reference robot poses that are associated with one or more tasks to be performed by the robot and are provided as inputs to the graph generation. Reference robot poses may be determined automatically based on computer analysis of the robot application or may be user-input values.

A robotic arm obstacle avoiding path planning method is provided. The method includes the following steps: step 1: simplifying the robotic arm model and obstacles, determining robotic arm joint points, and adopting virtual joint interpolation to interpolate connecting rods between adjacent joints; employing spherical bounding boxes at each joint point to envelop and replace the robotic arm model, enabling complete substitution for distance calculation when the robotic arm assumes any posture; step 2: adopting an eye-to-hand configuration to position the depth camera, acquiring in real time the point cloud information of the robotic arm and obstacles in the workspace, and using a robot real-time filtering package to filter out the point cloud information of the robotic arm itself.