Dynamically feasible trajectory planning for Anguilliform-inspired robots in the presence of steady ambient flow

• Published in: Robotics and autonomous systems Vol. 118; pp. 144 - 158
• Main Authors: Raj, Aditi, Thakur, Atul
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2019
• Subjects: Anguilliform-inspired robot; Fish-inspired robots; Flow; Heuristic function; Motion planning; Trajectory planning; Motion planning; Fish-inspired robots; Heuristic function; Trajectory planning; Anguilliform-inspired robot; Flow
• ISSN: 0921-8890; 1872-793X
• DOI: 10.1016/j.robot.2019.05.001

A crucial requirement for imparting autonomy to the fish-inspired robots is the trajectory planning capability that can generate obstacle-free and optimal trajectories to a commanded goal location. Research in the area of dynamics-aware trajectory planning, especially in the presence of environmental disturbances, for fish-inspired robots is scarce. Trajectory-following for fish-inspired robots, which is different from trajectory planning, has been well explored wherein feedback controllers that reject disturbances are employed to follow the pre-specified waypoints. This paper reports an optimal trajectory planning approach for Anguilliform-inspired robots based on model predictive planning framework. The robot’s dynamics constraints, as well as its interaction with the surrounding flow conditions, are captured via dynamics simulations and are expressed using discretized motion primitives. The motion primitives are then used for generating a search-tree and an A*-based algorithm is used for searching the optimal trajectory. We developed a simulation-based admissible heuristic function that is used for improving the computational performance of the developed trajectory planner. The developed simulation-based heuristic function provided a computational speed-up by a factor of up to 10.3 with respect to that of the Euclidean heuristic for test cases comprising of a variety of obstacle densities, ambient flow conditions, and goal locations. The trajectories generated by the developed approach have been found to be dynamically feasible, collision-free, and optimal for the experiments reported in this paper. We believe that the developed approach can impart autonomy to the Anguilliform-inspired robots that, due to their slender and hyper-redundant structures, can perform autonomous inspection and maintenance of sub-sea structures having narrow regions, obstacles, and ambient flow and can be useful in various civil and defense applications. •Trajectory planning amidst flow and obstacles for Anguilliform-inspired robots.•Simulation-based computation of dynamically feasible motion primitives.•A*-based optimal trajectory planning with simulation-based search heuristic.•Search speed-up by a factor of up to 10.3 over Euclidean-based heuristic.•Possible application in autonomous inspection and maintenance of sub-sea structures.