Extending obstacle avoidance methods through multiple parameter-space transformations

Abstract

Obstacle avoidance methods approach the problem of mobile robot autonomous navigation by steering the robot in real-time according to the most recent sensor readings, being suitable to dynamic or unknown environments. However, real-time performance is commonly gained by ignoring the robot shape and some or all of its kinematic restrictions which may lead to poor navigation performance in many practical situations.In this paper we propose a framework where a kinematically constrained and any-shape robot is transformed in real-time into a free-flying point in a new space where well-known obstacle avoidance methods are applicable. Our contribution with this framework is twofold: the definition of generalized space transformations that cover most of the existing transformational approaches, and a reactive navigation system where multiple transformations can be applied concurrently in order to optimize robot motion decisions. As a result, these transformations allow existing obstacle avoidance methods to perform better detection of the surrounding free-space, through "sampling" the space with paths compatible with the robot kinematics.We illustrate how to design these space transformations with some examples from our experience with real robots A shorter version of this article appeared in the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2006.navigating in indoor, cluttered, and dynamic scenarios. Also, we provide experimental results that demonstrate the advantages of our approach over previous methods when facing similar situations.

The Investigation of the Obstacle Avoidance for Mobile Robot Based on the Multi Sensor Information Fusion technology

“…Confirming the effectiveness of mentioned algorithm [9] In the research, we use the platform of autonomous mobile robot to do obstacle avoidance experiment. In the experiment, we use three cartons and one finishing tank as the obstacles.…”

The Hybrid Reciprocal Velocity Obstacle

“…Well-known reactive formulations include the dynamic window approach [3] and inevitable collision states [5], in addition to velocity obstacles [2]. Some approaches use a number of predefined discrete behaviors [10] or parameter space transformations [11]. Multiple robots may cooperate implicitly or by broadcasting their future intentions [12] or with limited bidirectional communication [13].…”

TP-Space RRT – Kinematic Path Planning of Non-Holonomic Any-Shape Vehicles

“…The TP-space was introduced in [8] as a generalization of space transformations that abstract the kinematics and shape of non-holonomic vehicles [21]. The basic idea behind those works is that the robot C-space can be partly charted by means of 2D manifolds in the parameter space of a family of trajectories (TP-space) -refer to Fig.…”

“…Such efficiency comes at a cost: planners may require a few seconds to generate a result for typical office-like navigation scenarios. This is in contrast to the ability of reactive methods to quickly respond to any dynamic change sensed in the environment, typically within one millisecond [8]. Current architectures for autonomous navigation tend to fuse global (planned) and local (reactive) methods, e.g., ROS navigation [9] and MoveIt!…”