This paper surveys recent developments in gross-motion planning, focusing on motion planners for point robots, rigid robots, and manipulators in various environments. It discusses the general issues in motion planning, recent approaches, and future research directions. Motion planning is classified as either gross or fine-motion planning. Gross-motion planning deals with large free spaces and positional errors, ensuring no collisions. Fine-motion planning handles narrow spaces requiring high accuracy. The paper reviews past work in computational geometry and robotics, and discusses possible future research directions. It covers the complexity of motion planning, classification of problems and algorithms, and the basic issues and steps in motion planning. The paper also discusses the computation of configuration obstacles, object sensing and representation, and approaches to motion planning. It highlights the importance of configuration space, the challenges of high-dimensional spaces, and the use of various methods such as skeleton, cell decomposition, potential field, and mathematical programming. The paper concludes with the complexity analysis of motion planning problems and the classification of motion-planning problems into static, dynamic, conformable, nonconformable, time-invariant, time-varying, and multimovers problems. The paper emphasizes the need for efficient motion planning algorithms and the challenges in solving motion planning problems due to high-dimensional configuration spaces and complex obstacles.This paper surveys recent developments in gross-motion planning, focusing on motion planners for point robots, rigid robots, and manipulators in various environments. It discusses the general issues in motion planning, recent approaches, and future research directions. Motion planning is classified as either gross or fine-motion planning. Gross-motion planning deals with large free spaces and positional errors, ensuring no collisions. Fine-motion planning handles narrow spaces requiring high accuracy. The paper reviews past work in computational geometry and robotics, and discusses possible future research directions. It covers the complexity of motion planning, classification of problems and algorithms, and the basic issues and steps in motion planning. The paper also discusses the computation of configuration obstacles, object sensing and representation, and approaches to motion planning. It highlights the importance of configuration space, the challenges of high-dimensional spaces, and the use of various methods such as skeleton, cell decomposition, potential field, and mathematical programming. The paper concludes with the complexity analysis of motion planning problems and the classification of motion-planning problems into static, dynamic, conformable, nonconformable, time-invariant, time-varying, and multimovers problems. The paper emphasizes the need for efficient motion planning algorithms and the challenges in solving motion planning problems due to high-dimensional configuration spaces and complex obstacles.