Road-following formation control of autonomous ground vehicles

Abstract

This work presents a novel cooperative path planning for formation keeping robots traversing along a road with obstacles and possible narrow passages. A unique challenge in this problem is a requirement for spatial and temporal coordination between vehicles while ensuring collision and obstacle avoidance. A two-step approach is used for fast realtime planning. The first step uses the A* search on a spatiotemporally extended graph to generate an obstacle-free path for the agent while the second step refines this path through local optimization to comply with dynamic and other vehicle constraints. This approach keeps robots close to their intended formation while giving them flexibility to negotiate narrow passages and obstacles, adhering to any given constraints.

Self-Triggered Formation Control of Nonholonomic Robots

“…In our example, we set dL1=10.166667emnormalm and dL2=dL3=0.40.166667emnormalm. To implement the spatially coordinated road-following formation [35], delayed velocity references of the Virtual Leader are sent to the robots depending on the longitudinal distance from the robot to the Virtual Leader, and adjusted linear velocity references for the Virtual Leader are sent to the robots depending on the curvature of the route in each track and the lateral distance from the robot to the Virtual Leader. In the formation shown in Figure 3, Robot 1 receives the delayed velocity reference and Robot 2 and Robot 3 the references adjusted for the curvature of each track.…”

“…Road-following formation allows two kinds of coordination: the spatial coordination and temporal coordination [35]. In the case of spatial coordination, the trajectories of each unit within the formation are coordinated, thus the shape of formation adapts to the conditions of the trajectory; therefore, the distances between the different agents of the formation can vary at certain times.…”

A distributed MPC framework for road-following formation control of car-like vehicles

“…The first scenario involves three vehicles in a triangleshaped formation (Fig. 2) which can be used, for instance, for a snowplowing application [4]. The desired formation remains static during the entire simulation, while vehicles must avoid on-road obstacles and cross narrow corridors.…”

“…Moreover, the formation is determined in advance and cannot be reconfigured. Other approaches include Laplacianbased control [14], graph searching methods [4], etc.. This paper proposes and validates a novel on-road formation control framework established on the theoretical results of distributed MPC, upon which we propose multiple adaptations to handle the challenges raised by the on-road driving setting.…”

Partitioning of the free space-time for on-road navigation of autonomous ground vehicles

“…By contrast, our method can be applied in many scenarios (including highway and urban driving, for instance crossing an intersection) with the same formalism. Although spatio-temporal graphs have already been used for the control of AGVs [18], [19], no existing approach provides the same desirable properties, and notably to easily account for margins in planning.…”