A novel obstacle avoidance algorithm:“Follow the Gap Method"
In this paper, a novel obstacle avoidance method is designed and applied to an experimental autonomous ground vehicle system. The proposed method brings a new solution to the problem and has several advantages compared to previous methods. This novel algorithm is easy to tune and it takes into consideration the field of view and the nonholonomic constraints of the robot. Moreover the method does not have a local minimum problem and results in safer trajectories because of its inherent properties in the definition of the algorithm. The proposed algorithm is tested in simulations and after the observation of successful results, experimental tests are performed using static and dynamic obstacle scenarios. The experimental test platform is an autonomous ground vehicle with Ackermann steering geometry which brings nonholonomic constraints to the vehicle. Experimental results show that the task of obstacle avoidance can be achieved using the algorithm on the autonomous vehicle platform. The algorithm is very promising for application in mobile and industrial robotics where obstacle avoidance is a feature of the robotic system.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Cooperative Sensing Enhanced UAV Path-Following and Obstacle Avoidance with Variable Formation
The high mobility of unmanned aerial vehicles (UAVs) enables them to be used in various civilian fields, such as rescue and cargo transport. Path-following is a crucial way to perform these tasks while sensing and collis…
Reinforcement LearningCollision AvoidanceMulti-UAV Swarm Obstacle Avoidance Based on Potential Field Optimization
In multi UAV scenarios,the traditional Artificial Potential Field (APF) method often leads to redundant flight paths and frequent abrupt heading changes due to unreasonable obstacle avoidance path planning,and is highly …
Sample Efficient Learning of Path Following and Obstacle Avoidance Behavior for Quadrotors
In this paper we propose an algorithm for the training of neural network control policies for quadrotors. The learned control policy computes control commands directly from sensor inputs and is hence computationally effi…
Collision AvoidanceImitation LearningOn the Dual Implementation of Collision-Avoidance Constraints in Path-Following MPC for Underactuated Surface Vessels
A path-following collision-avoidance model predictive control (MPC) method is proposed which approximates obstacle shapes as convex polygons. Collision-avoidance is ensured by means of the signed distance function which …
Collision AvoidanceModel Predictive ControlRFPPO: Motion Dynamic RRT based Fluid Field - PPO for Dynamic TF/TA Routing Planning
Existing local dynamic route planning algorithms, when directly applied to terrain following/terrain avoidance, or dynamic obstacle avoidance for large and medium-sized fixed-wing aircraft, fail to simultaneously meet th…
Trajectory Planning