Trajectory Planning and Obstacle Avoidance for Hyper-Redundant Serial Robots

Abstract

Hyper-redundant snakelike serial robots are of great interest due to their application in search and rescue during disaster relief in highly cluttered environments and recently in the field of medical robotics. A key feature of these robots is the presence of a large number of redundant actuated joints and the associated well-known challenge of motion planning. This problem is even more acute in the presence of obstacles. Obstacle avoidance for point bodies, nonredundant serial robots with a few links and joints, and wheeled mobile robots has been extensively studied, and several mature implementations are available. However, obstacle avoidance for hyper-redundant snakelike robots and other extended articulated bodies is less studied and is still evolving. This paper presents a novel optimization algorithm, derived using calculus of variation, for the motion planning of a hyper-redundant robot where the motion of one end (head) is an arbitrary desired path. The algorithm computes the motion of all the joints in the hyper-redundant robot in a way such that all its links avoid all obstacles present in the environment. The algorithm is purely geometric in nature, and it is shown that the motion in free space and in the vicinity of obstacles appears to be more natural. The paper presents the general theoretical development and numerical simulations results. It also presents validating results from experiments with a 12-degree-of-freedom (DOF) planar hyper-redundant robot moving in a known obstacle field.

Minimally actuated hyper-redundant robots: Motion planning methods based on fractals and self-organizing systems

“…Recent works have addressed obstacle avoidance schemes for hyper-redundant robots. State-of-the-art approaches including genetic algorithms, [12][13][14] variational methods, 15,16 evolutionary algorithms, 17 potential fields, 18 and probabilistic road maps 19 are used to plan the motions of the robots. Other sophisticated techniques are described by Pan and Yu 20 and Pan et al 21 Contemporary motion planners based on rapidly exploring random search trees work by having to "fill" an N-dimensional configuration space with nodes representing allowable robot configurations.…”

Set-based path following and obstacle avoidance for underwater snake robots

“…While [7,8] consider mainly local obstacle detection, the study in [9] requires a global map of the obstacle locations a priori. For terrestrial snake robots, obstacle avoidance strategies have been considered in [10][11][12]. In [10], a control strategy for a terrestrial snake robot with passive wheels is presented, where obstacles in the way of the robot are avoided by altering the sinusoidal shape that the robot adapts to.…”

“…A similar strategy for moving obstacles is proposed and experimentally validated in [11], where a robot is remotely controlled to move forward and avoids obstacles on the way by lifting links that are about to collide sideways. In [12], a method for both trajectory planning and obstacle avoidance is proposed. However, the method in [12] is for snake robots with active wheels, and thus not applicable for underwater snake robots.…”

“…In [12], a method for both trajectory planning and obstacle avoidance is proposed. However, the method in [12] is for snake robots with active wheels, and thus not applicable for underwater snake robots. There is a lot of literature on obstacle avoidance that is not specific for snake robots, see for instance the reviews on mobile robots [13], unmanned aerial vehicles [14], or autonomous ships [15].…”

Analysis of the Computational Complexity of the Method of Iterative Dimensional-Linear Generation of the Trajectory of Motion of the Three-Line Anthropomorphic Manipulator in the Volume Space With Obstruction

“…Планирование траектории движения избыточных манипуляторов на основе эволюционных подходов рассмотрено в работах [2][3][4][5][6][7]. Предлагаемые решения нацелены на получение точного решения как в офлайн режиме, так и в режиме реального времени, но при этом не учитывают энергопотребление двигателей манипулятора при перемещении.…”