A framework for safe human-humanoid coexistence

This work is focused on the development of a safety framework for Human-Humanoid coexistence, with emphasis on humanoid locomotion. After a brief introduction to the fundamental concepts of humanoid locomotion, the two most common approaches for gait generation are presented, and are extended with the inclusion of a stability condition to guarantee the boundedness of the generated trajectories. Then the safety framework is presented, with the introduction of different safety behaviors. These behaviors are meant to enhance the overall level of safety during any robot operation. Proactive behaviors will enhance or adapt the current robot operations to reduce the risk of danger, while override behaviors will stop the current robot activity in order to take action against a particularly dangerous situation. A state machine is defined to control the transitions between the behaviors. The behaviors that are strictly related to locomotion are subsequently detailed, and an implementation is proposed and validated. A possible implementation of the remaining behaviors is proposed through the review of related works that can be found in literature

A novel coordination framework for multi-robot systems

Having made great progress tackling the basic problems concerning single-robot systems, many researchers shifted their focus towards the study of multi-robot systems (MRS). MRS were shortly found to be a perfect t for tasks considered to be hard, complex or even impossible for a single robot to perform, e.g. spatially separate tasks. One core research problem of MRS is robots' coordinated motion planning and control. Arti cial potential elds (APFs) and virtual spring-damper bonds are among the most commonly used models to attack the trajectory planning problem of MRS coordination. However, although mathematically sound, these approaches fail to guarantee inter-robot collision-free path generation. This is particularly the case when robots' dynamics, nonholonomic constraints and complex geometry are taken into account. In this thesis, a novel bio-inspired collision avoidance framework via virtual shells is proposed and augmented into the high-level trajectory planner. Safe trajectories can hence be generated for the low-level controllers to track. Motion control is handled by the design of hierarchical controllers which utilize virtual inputs. Several distinct coordinated task scenarios for 2D and 3D environments are presented as a proof of concept. Simulations are conducted with groups of three, four, ve and ten nonholonomic mobile robots as well as groups of three and ve quadrotor UAVs. The performance of the overall improved coordination structure is veri ed with very promising result

Formation control for cooperative surveillance

Constructing and maintaining a formation is critical in applications of cooperative control of multi-agent systems. In this research we address the formation control problem of generating a formation for a group of nonholonomic mobile agents. The formation control scheme proposed in this work is based on a fusion of leader-follower and virtual reference approaches. This scheme gives a formation constraint representation that is independent of the number of agents in the formation and the resulting control algorithm is scalable. One of the important desired features in controller design is that the formation errors defined by formation constraints should be stabilized globally and exponentially by the controller. The proposed controller is based on feedback linearization, and formation errors are shown to be globally exponentially stable in the sense of Lyapunov. Since formation errors are stabilized globally, the proposed controller is applicable to both formation keeping and formation construction problems. As a possible application, the proposed algorithm is implemented in a cooperative ground moving target surveillance scenario. The proposed algorithm enables the determination of the minimal number of agents required for surveillance of a moving target. The number of agents returned by this scheme is not optimal and hence is a conservative solution. However, this is justified by the computational savings the scheme offers

Dynamic path following controllers for planar mobile robots

In the field of mobile robotics, many applications require feedback control laws that provide perfect path following. Previous work has shown that transverse feedback linearization is an effective approach to designing path following controllers that achieve perfect path following and path invariance. This thesis uses transverse feedback linearization and augments it with dynamic extension to present a framework for designing path following controllers for certain kinematic models of mobile robots. This approach can be used to design path following controllers for a large class of paths. While transverse feedback linearization makes the desired path attractive and invariant, dynamic extension allows the closed-loop system to achieve the desired motion along the path. In particular, dynamic extension can be used to make the mobile robot track a desired velocity or acceleration profile while moving along a path

Adaptive robust control of an omnidirectional mobile platform for autonomous service robots in polar coordinates

This paper presents an adaptive robust control method for trajectory tracking and path following of an omni-directional wheeled mobile platform with actuators' uncertainties. The polar-space kinematic model of the platform with three independent driving omnidirectional wheels equally spaced at 120 from one another is briefly introduced, and the dynamic models of the three uncertain servomotors mounted on the driving wheels are also described. With the platform's kinematic model and the motors' dynamic model associated two unknown parameters, the adaptive robust controller is synthesized via the integral backstepping approach. Computer simulations and experimental results are conducted to show the effectiveness and merits of the proposed control method in comparison with a conventional PI feedback control method