Window-shaped obstacle avoidance for a redundant manipulator.

Area of Science:

• Robotics
• Control Systems
• Artificial Intelligence

Background:

• Obstacle avoidance is crucial for robotic systems operating in complex environments.
• Existing methods, like Zghal's, have limitations in handling window-shaped obstacles, leading to undesirable joint rate chatter.
• The precise calculation of the shortest distance between manipulator links and obstacle edges is a key challenge.

Purpose of the Study:

• To address the shortcomings of existing window-shaped obstacle avoidance methods.
• To propose a novel scheme for calculating the shortest distance between manipulator links and window edges.
• To develop an improved method, the Nearest Link (NL) method, for enhanced obstacle avoidance performance.

Main Methods:

• A new scheme is proposed to accurately determine the shortest distance, mitigating the chattering problem.
• The Nearest Link (NL) method is introduced, focusing on the nearest manipulator link for performance criterion.
• Comparative analysis of the proposed NL method against Zghal's method for window-shaped obstacle avoidance.

Main Results:

• The proposed shortest distance scheme effectively remedies the chattering problem in joint rates.
• The NL method eliminates the on-line weighting assignment issue present in Zghal's method.
• The NL method requires less redundancy for obstacle avoidance, enabling greater redundancy for other tasks.

Conclusions:

• The developed NL method offers a significant improvement over Zghal's approach for 3-D window-shaped obstacle avoidance.
• The NL method enhances robotic control by providing smoother joint rate trajectories and reducing computational complexity.
• This advancement facilitates more efficient and versatile robotic applications in dynamic environments.