This paper proposes a fully-distributed control protocol that achieves time-varying group formation tracking for linear multi-agent systems connected via directed graph. The group formation tracking often leads to sub-formations especially when the leaders are placed far apart or they have separate control inputs. In the proposed approach, the followers are distributed into several subgroups and each subgroup attains the predefined sub-formation along with encompassing the leaders. Each subgroup can be assigned multiple leaders, contrary to the single-leader case considered in most of the existing literature, which makes the current problem non-trivial. When multiple leaders exist in a subgroup, the sub-formation attained by that subgroup keeps tracking a convex combination of the states of the leaders. A distributed adaptive control protocol has been introduced in this paper which uses only relative state information and thus avoids direct computation of the graph Laplacian matrix. Due to virtue of this, the proposed scheme remains effective even when some of the agents get disconnected from the network due to sudden communication failure. An algorithm is provided to outline the steps to design the control law to attain time-varying group formation tracking with multiple leaders. Towards the end, a case study on multi-target surveillance operation is taken up to show an important application of the proposed adaptive control technique.

Cooperative control of multirobot systems (MRSs) has earned significant research interest over the past two decades due to its potential applications in multidisciplinary engineering problems. In contrast to a single specialized robot, the MRS can be designed to offer flexibility, reconfigurability, robustness to faults, and cost-effectiveness in solving complex and challenging tasks. In this article, we aim to develop a unified cluster formation containment coordination framework for networked robots that can be decomposed into two layers containing the leaders and the followers. According to the proposed methodology, the leader robots are first distributed into a set of distinct and nonoverlapping clusters depending on the positions and priorities of the targets exploiting a game-theoretic rule. Then, they are steered to attain the desired formations around the corresponding targets. Subsequently, the follower robots are made to converge into the convex hull spanned by the leaders of the individual clusters. A prototype search and rescue operation is considered to highlight the usefulness of the proposed coordination framework. Furthermore, real-time hardware experiments were conducted on miniature mobile robots to validate the feasibility of the theoretical results.

Autonomous driving of multi-lane vehicle platoons have attracted significant attention in recent years due to their potential to enhance the traffic-carrying capacity of the roads and produce better safety for drivers and passengers. This paper proposes a distributed motion planning algorithm to ensure safe overtaking of autonomous vehicles in a dynamic environment using the Artificial Potential Field method. Unlike the conventional overtaking techniques, autonomous driving strategies can be used to implement safe overtaking via formation control of unmanned vehicles in a complex vehicle platoon in the presence of human-operated vehicles. Firstly, we formulate the overtaking problem of a group of autonomous vehicles into a multi-target tracking problem, where the targets are dynamic. To model a multi-vehicle system consisting of both autonomous and human-operated vehicles, we introduce the notion of velocity difference potential field and acceleration difference potential field. We then analyze the stability of the multi-lane vehicle platoon and propose an optimization-based algorithm for solving the overtaking problem by placing a dynamic target in the traditional artificial potential field. A simulation case study has been performed to verify the feasibility and effectiveness of the proposed distributed motion control strategy for safe overtaking in a multi-lane vehicle platoon.

Inspired by the group activities of natural swarms (e.g., a flock of birds, a colony of ants, etc.), a fleet of mobile robots can be collaboratively put into work to accomplish complex real-world tasks. Depending on the nature and complexity of a problem, a multi-robot system (MRS) may need to be decomposed into several subgroups. This paper proposes a unified group coordinated control scheme for networked MRSs having multiple targets. A `discontinuous' cooperative control law is first developed for a networked MRS to achieve individual sub-formations surrounding the assigned targets. A `continuous' cooperative control protocol is then proposed to overcome the chattering phenomenon often caused by a discontinuous control action during hardware implementation. The closed-loop stability of the overall networked MRS is guaranteed via the Lyapunov theory and boundary-layer techniques. Finally, two hardware experiments (target-enclosing and object transportation) involving real mobile robots have been carried out to demonstrate the usefulness of the proposed scheme.