Rama Seshan Chandrasekaran

Bio: Rama Seshan Chandrasekaran is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Collision & Obstacle avoidance. The author has an hindex of 2, co-authored 2 publications receiving 9 citations.

Variational collision and obstacle avoidance of multi-agent systems on Riemannian manifolds.

Abstract: In this paper we study a path planning problem from a variational approach to collision and obstacle avoidance for multi-agent systems evolving on a Riemannian manifold. The problem consists of finding non-intersecting trajectories between the agent and prescribed obstacles on the workspace, among a set of admissible curves, to reach a specified configuration, based on minimizing an energy functional that depends on the velocity, covariant acceleration and an artificial potential function used to prevent collision with the obstacles and among the agents. We apply the results to examples of a planar rigid body, and collision and obstacle avoidance for agents evolving on a sphere.

Variational collision and obstacle avoidance of multi-agent systems on Riemannian manifolds

Abstract: In this paper we study a path planning problem from a variational approach to collision and obstacle avoidance for multi-agent systems evolving on a Riemannian manifold. The problem consists of finding non-intersecting trajectories between the agent and prescribed obstacles on the workspace, among a set of admissible curves, to reach a specified configuration, based on minimizing an energy functional that depends on the velocity, covariant acceleration and an artificial potential function used to prevent collision with the obstacles and among the agents. We apply the results to examples of a planar rigid body, and collision and obstacle avoidance for agents evolving on a sphere.

Local minimizers for variational obstacle avoidance on Riemannian manifolds

Abstract: This paper studies a variational obstacle avoidance problem on complete Riemannian manifolds. That is, we minimize an action functional, among a set of admissible curves, which depends on an artificial potential function used to avoid obstacles. In particular, we generalize the theory of bi-Jacobi fields and biconjugate points and present necessary and sufficient conditions for optimality. Local minimizers of the action functional are divided into two categories—called $ Q $-local minimizers and $ \Omega $-local minimizers—and subsequently classified, with local uniqueness results obtained in both cases.

A Decentralized Strategy for Variational Collision Avoidance on Complete Riemannian Manifolds

Abstract: We introduce a variational approach for decentralized collision avoidance of multiple agents evolving on a Riemannian manifold, and we derive necessary conditions for extremal. The problem consists of finding non-intersecting trajectories of a given number of agents sharing only the information of relative positions with respect to their nearest neighbors, among a set of admissible curves, such that these trajectories are minimizers of an energy functional. The energy functional depends on covariant acceleration and an artificial potential used to prevent collision among the agents. We show the global existence of extrema for the energy functional. We apply the results to the case of agents on a compact and connected Lie group. Simulation results are shown to demonstrate the applicability of the results.

Variational problems on Riemannian manifolds with constrained accelerations

Abstract: We introduce variational problems on Riemannian manifolds with constrained acceleration and derive necessary conditions for normal extremals in the constrained variational problem. The problem consists on minimizing a higher-order energy functional, among a set of admissible curves defined by a constraint on the covariant acceleration. In addition, we use this framework to address the elastic splines problem with obstacle avoidance in the presence of this type of contraints.

Obstacle Avoidance for Formation Systems under Hamel’s formalism

Abstract: We consider the obstacle avoidance problem of formation vehicles in an obstacle laden environment. Two control forces, formation keeping force and generalized Lorentz force, are proposed to adaptively maintain the formation pattern while avoiding obstacles. The methods result in a flexible overall obstacle avoidance effect for formation systems demonstrated by numerical simulations.