Exploring Robot Trajectory Planning -- A Comparative Analysis of Algorithms And Software Implementations in Dynamic Environments

TL;DR

This paper compares various trajectory planning algorithms and software implementations in dynamic environments, highlighting challenges like adaptability and real-time analysis in robotics applications.

Contribution

It provides a comprehensive comparative analysis of trajectory planning algorithms and software strategies for dynamic and unpredictable environments.

Findings

Identifies key challenges in real-time trajectory planning

Analyzes effectiveness of different algorithms in dynamic settings

Highlights importance of adaptability in robotic motion control

Abstract

Trajectory Planning is a crucial word in Modern & Advanced Robotics. It's a way of generating a smooth and feasible path for the robot to follow over time. The process primarily takes several factors to generate the path, such as velocity, acceleration and jerk. The process deals with how the robot can follow a desired motion path in a suitable environment. This trajectory planning is extensively used in Automobile Industrial Robot, Manipulators, and Mobile Robots. Trajectory planning is a fundamental component of motion control systems. To perform tasks like pick and place operations, assembly, welding, painting, path following, and obstacle avoidance. This paper introduces a comparative analysis of trajectory planning algorithms and their key software elements working strategy in complex and dynamic environments. Adaptability and real-time analysis are the most common problems in trajectory planning. The paper primarily focuses on getting a better understanding of these unpredictable environments.