Robotic Manipulator Trajectory Planning With Visual Obstacle Correction
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Solution Overview
Problem
Conventional robotic manipulators lack the capability to plan motion trajectories autonomously and flexibly, especially in complex scenarios such as elderly care, assistance for people in need, family services, and human-machine collaboration, where they struggle with obstacle avoidance and adapting to dynamic environments.
Innovation Solution
A method for robotic manipulators that involves a processor and storage unit executing computer programs to plan motion trajectories using a visual inspection system, a dynamical system model, and a teaching motion library, allowing for obstacle avoidance corrections based on environmental data and command instructions, enabling autonomous and flexible movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional robotic manipulators use traditional control methods, then the device structure is simple, but the ability to autonomously plan motion trajectories and adapt to complex scenarios is insufficient
Solution Approach 1:
The motion trajectory planning is divided into multiple discrete key points (first key point, second key point, etc.) along the trajectory. Each key point represents a specific position and posture that the manipulator needs to achieve. This segmentation allows the complex planning problem to be broken down into manageable segments that can be processed independently and sequentially.
Solution Approach 2:
The system pre-calculates and stores motion trajectory planning data including multiple key points with their respective positions, postures, and timing information before actual execution. This preliminary action enables the manipulator to have a ready-made plan for common scenarios, reducing real-time computational burden and improving response speed while maintaining adaptability.
2Adaptability or versatility
If conventional robotic manipulators use fixed motion patterns, then the control system is simple, but the flexibility in complex scenarios like elderly care and human-machine collaboration is limited
Solution Approach 1:
The motion trajectory planning system dynamically adjusts key points based on real-time environmental feedback and task requirements. The system can add, remove, or modify key points along the trajectory depending on obstacles detected, task changes, or human interaction needs. This dynamic adjustment capability provides flexibility in complex scenarios while maintaining a high level of automation.
Solution Approach 2:
The system incorporates feedback mechanisms where the actual execution of motion trajectories is monitored and compared against the planned path. Based on this feedback, the system can automatically adjust subsequent key points and trajectory parameters to handle unexpected situations such as obstacles, human presence, or task modifications, enhancing adaptability in elderly care and human-machine collaboration scenarios.
3Manufacturing precision
If the robotic manipulator uses detailed motion trajectory planning with multiple key points, then the motion precision is improved, but the computational time and processing load increase
Solution Approach 1:
The system uses a hierarchical approach where not all key points are processed with equal detail. Critical key points that require high precision (such as those involving human interaction or delicate tasks) are calculated with greater accuracy, while less critical segments use coarser approximation. This partial action approach maintains necessary precision where needed while reducing overall computational time.
Solution Approach 2:
Motion trajectory planning data including multiple key points with their respective positions, postures, and timing information is pre-calculated and stored for common scenarios and standard tasks. This preliminary computation reduces real-time processing requirements, allowing the system to achieve high motion precision without excessive computational time during actual execution.
Data Source
AI summary
A motion trajectory planning method for a robotic manipulator having a visual inspection system, includes: in response to a command instruction, obtaining environmental data collected by the visual inspection system; determining an initial DS model motion trajectory of the robotic manipulator according to the command instruction, the environmental data, and a preset teaching motion DS model library, wherein the teaching motion DS model library includes at least one DS model motion trajectory generated based on human teaching activities; and at least based on a result of determining whether there is an obstacle, whose pose is on the initial DS model motion trajectory, in a first object included in the environmental data, correcting the initial DS model motion trajectory to obtain a desired motion trajectory of the robotic manipulator.