112 research outputs found
Defend the practicality of single-integrator models in multi-robot coordination control
Single-integrator models have been widely used to model robot kinematics in multi-robot coordination control problems. However, it is also widely believed that this model is too simple to lead to practically useful control laws. In this paper, we prove that if a gradient-descent distributed control law designed for single integrators has been proved to be convergent for a given coordination task, then the control law can be readily modified to adapt for various motion constraints including velocity saturation, obstacle avoidance, and nonholonomic models. This result is valid for a wide range of coordination tasks. It defends the practical usefulness of many existing coordination control laws designed based on single-integrator models and suggests a new methodology to design coordination control laws subject motion constraints
A general approach to coordination control of mobile agents with motion constraints
This paper proposes a general approach to design convergent
coordination control laws for multi-agent systems subject to
motion constraints. The main contribution of this paper is to prove
in a constructive way that a gradient-descent coordination control law
designed for single integrators can be easily modified to adapt for various
motion constraints such as nonholonomic dynamics, linear/angular
velocity saturation, and other path constraints while preserving the
convergence of the entire multi-agent system. The proposed approach is
applicable to a wide range of coordination tasks such as rendezvous and
formation control in two and three dimensions. As a special application,
the proposed approach solves the problem of distance-based formation
control subject to nonholonomic and velocity saturation constraints
Cooperative Target Tracking in Balanced Circular and Elliptical Formations
This paper extends our earlier results on cooperative target tracking in cyclic pursuit using a group of mobile robots by further prescribing the formation radius and achieving an elliptical formation pattern. Prescribing the formation radius of a balanced circular formation is achieved by adjusting a parameter in the existing control input to each robot. The new elliptical formation pattern is obtained via a transformation matrix. Both single-integrator and double-integrator robot models are considered. The effectiveness of the proposed schemes is demonstrated by simulation examples
Safety-Critical Coordination for Cooperative Legged Locomotion via Control Barrier Functions
This paper presents a safety-critical approach to the coordinated control of
cooperative robots locomoting in the presence of fixed (holonomic) constraints.
To this end, we leverage control barrier functions (CBFs) to ensure the safe
cooperation of the robots while maintaining a desired formation and avoiding
obstacles. The top-level planner generates a set of feasible trajectories,
accounting for both kinematic constraints between the robots and physical
constraints of the environment. This planner leverages CBFs to ensure
safety-critical coordination control, i.e., guarantee safety of the
collaborative robots during locomotion. The middle-level trajectory planner
incorporates interconnected single rigid body (SRB) dynamics to generate
optimal ground reaction forces (GRFs) to track the safety-ensured trajectories
from the top-level planner while addressing the interconnection dynamics
between agents. Distributed low-level controllers generate whole-body motion to
follow the prescribed optimal GRFs while ensuring the friction cone condition
at each end of the stance legs. The effectiveness of the approach is
demonstrated through numerical simulations and experimentally on a pair of
quadrupedal robots.Comment: Under revie
Multi-agent Collision Avoidance Using Interval Analysis and Symbolic Modelling with its Application to the Novel Polycopter
Coordination is fundamental component of autonomy when a system is defined by multiple mobile agents. For unmanned aerial systems (UAS), challenges originate from their low-level systems, such as their flight dynamics, which are often complex. The thesis begins by examining these low-level dynamics in an analysis of several well known UAS using a novel symbolic component-based framework. It is shown how this approach is used effectively to define key model and performance properties necessary of UAS trajectory control. This is demonstrated initially under the context of linear quadratic regulation (LQR) and model predictive control (MPC) of a quadcopter.
The symbolic framework is later extended in the proposal of a novel UAS platform, referred to as the ``Polycopter" for its morphing nature. This dual-tilt axis system has unique authority over is thrust vector, in addition to an ability to actively augment its stability and aerodynamic characteristics. This presents several opportunities in exploitative control design.
With an approach to low-level UAS modelling and control proposed, the focus of the thesis shifts to investigate the challenges associated with local trajectory generation for the purpose of multi-agent collision avoidance. This begins with a novel survey of the state-of-the-art geometric approaches with respect to performance, scalability and tolerance to uncertainty. From this survey, the interval avoidance (IA) method is proposed, to incorporate trajectory uncertainty in the geometric derivation of escape trajectories. The method is shown to be more effective in ensuring safe separation in several of the presented conditions, however performance is shown to deteriorate in denser conflicts.
Finally, it is shown how by re-framing the IA problem, three dimensional (3D) collision avoidance is achieved. The novel 3D IA method is shown to out perform the original method in three conflict cases by maintaining separation under the effects of uncertainty and in scenarios with multiple obstacles. The performance, scalability and uncertainty tolerance of each presented method is then examined in a set of scenarios resembling typical coordinated UAS operations in an exhaustive Monte-Carlo analysis
Agent-based models of social behaviour and communication in evacuations: A systematic review
Most modern agent-based evacuation models involve interactions between
evacuees. However, the assumed reasons for interactions and portrayal of them
may be overly simple. Research from social psychology suggests that people
interact and communicate with one another when evacuating and evacuee response
is impacted by the way information is communicated. Thus, we conducted a
systematic review of agent-based evacuation models to identify 1) how social
interactions and communication approaches between agents are simulated, and 2)
what key variables related to evacuation are addressed in these models. We
searched Web of Science and ScienceDirect to identify articles that simulated
information exchange between agents during evacuations, and social behaviour
during evacuations. From the final 70 included articles, we categorised eight
types of social interaction that increased in social complexity from collision
avoidance to social influence based on strength of social connections with
other agents. In the 17 models which simulated communication, we categorised
four ways that agents communicate information: spatially through information
trails or radii around agents, via social networks and via external
communication. Finally, the variables either manipulated or measured in the
models were categorised into the following groups: environmental condition,
personal attributes of the agents, procedure, and source of information. We
discuss promising directions for agent-based evacuation models to capture the
effects of communication and group dynamics on evacuee behaviour. Moreover, we
demonstrate how communication and group dynamics may impact the variables
commonly used in agent-based evacuation models.Comment: Pre-print submitted to Safety Science special issue following the
2023 Pedestrian and Evacuation Dynamics conferenc
Agent-based models of social behaviour and communication in evacuations:A systematic review
Most modern agent-based evacuation models involve interactions between evacuees. However, the assumed reasons for interactions and portrayal of them may be overly simple. Research from social psychology suggests that people interact and communicate with one another when evacuating and evacuee response is impacted by the way information is communicated. Thus, we conducted a systematic review of agent-based evacuation models to identify 1) how social interactions and communication approaches between agents are simulated, and 2) what key variables related to evacuation are addressed in these models. We searched Web of Science and ScienceDirect to identify articles that simulated information exchange between agents during evacuations, and social behaviour during evacuations. From the final 70 included articles, we categorised eight types of social interaction that increased in social complexity from collision avoidance to social influence based on strength of social connections with other agents. In the 17 models which simulated communication, we categorised four ways that agents communicate information: spatially through information trails or radii around agents, via social networks and via external communication. Finally, the variables either manipulated or measured in the models were categorised into the following groups: environmental condition, personal attributes of the agents, procedure, and source of information. We discuss promising directions for agent-based evacuation models to capture the effects of communication and group dynamics on evacuee behaviour. Moreover, we demonstrate how communication and group dynamics may impact the variables commonly used in agent-based evacuation models
- …