Autonomous Bicycle Research Articles

Business models on the basis of digital infrastructure data

The project Ready for Smart City Robots (R4R) is developing strategies for the detailed capture of infrastructural environmental parameters. These are intended to be utilized for autonomous mobility and logistics applications on pedestrian and bicycle paths. The project evaluates the quality and completeness of data for Smart City concepts, using examples from (autonomous) micro-mobility in logistics and transportation. The results encompass the following areas: firstly, the identification of necessary environmental information for environmentally friendly, automated last-mile logistics, along with a continuous data collection method for up-to-date information. Secondly, the examination of various integration scenarios for autonomous delivery services and an autonomous bicycle rental system in rural areas. This includes the development of application scenarios and the scientific support of the prototype construction of the necessary technical prerequisites for the data/sensor boxes. The following outlines the business model potentials for data collection, autonomous micro-mobility, sharing services, and Smart City applications.

Steering control and stability analysis for an autonomous bicycle: part II experiments and a modified linear control law

Steering control and stability analysis for an autonomous bicycle: part II experiments and a modified linear control law

Data-Driven Approach for Defining Demand Scenarios for Shared Autonomous Cargo Bike Fleets

Bike sharing systems have become a sustainable alternative to motorized private transport in urban areas. However, users often face high costs and availability issues due to the operational effort required to redistribute bicycles between stations. For addressing those issues, the AuRa (Autonomes Rad, Eng. Autonomous Bicycle) project introduces a new mobility offer in terms of an on-demand, shared-use, self-driving cargo bikes service (OSABS) that enables automated redistribution. Within the project, we develop different order management and rebalancing strategies and validate them using simulation models. One prerequisite for this is sound demand scenarios. However, due to the novelty of OSABS, there is currently no information about its utilization. Consequently, the objective of this study was to develop an approach for defining OSABS demand scenarios in a temporally and spatially disaggregated manner as an input for simulation models. Therefore, we first derived city-wide usage potentials of OSABS from a survey on mobility needs. We then spatially and temporally disaggregated the determined usage likelihood using travel demand matrices and usage patterns from a conventional bike-sharing system, respectively. Finally, we performed cluster analyses on the resulting annual demand to summarize sections of the yearly profile into representative units and thus reduce the simulation effort. As we applied this approach as a case study to the city of Magdeburg, Germany, we could show that our methodology enables the determination of reasonable OSABS demand scenarios from scratch. Furthermore, we were able to show that annual usage patterns of (conventional) bike sharing systems can be modeled by using demand data for only eight representative weeks.

On the Initialization Problem for Timed-Elastic Bands

Path planning is an important part of navigation for mobile robots. Several approaches have been proposed in the literature based on a discretisation of the map, including A*, Theta*, and RRT*. While these approaches have been widely adopted also in real applications, they tend to generate non-smooth paths, which can be difficult to follow, based on the kinematic and dynamic constraints of the robot. Time-Elastic-Bands (TEB) have also been used in the literature, to deform an original path in real-time to produce a smoother path, and to handle potential local changes in the environment, such as the detection of an unknown obstacle. This work analyses the effects on the overall path for different choices of initial paths fed to TEB. In particular, the produced paths are compared in terms of total distance, curvature, and variation in the desired heading. The optimised version of the solution produced by Theta* shows the highest performance among the considered methods and metrics, and we show that it can be successfully followed by an autonomous bicycle.

Control and Trajectory Planning of an Autonomous Bicycle Robot

This paper addresses the modeling and the control of an autonomous bicycle robot where the reference point is the center of gravity. The controls are based on the wheel heading’s angular velocity and the steering’s angular velocity. They have been developed to drive the autonomous bicycle robot from a given initial state to a final state, so that the total running cost is minimized. To solve the problem, the following approach was used: after having computed the control system Hamiltonian, Pontryagin’s Minimum Principle was applied to derive the feasible controls and the costate system of ordinary differential equations. The feasible controls, derived as functions of the state and costate variables, were substituted into the combined nonlinear state–costate system of ordinary differential equations and yielded a control-free, state–costate system of ordinary differential equations. Such a system was judiciously vectorized to easily enable the application of any computer program written in Matlab, Octave or Scilab. A Matlab computer program, set as the main program, was developed to call a Runge–Kutta function coded into Matlab to solve the combined control-free, state–costate system of ordinary differential equations coded into a Matlab function. After running the program, the following results were obtained: seven feasible state functions from which the feasible trajectory of the robot is derived, seven feasible costate functions, and two feasible control functions. Computational simulations were developed and provided in order to persuade the readers of the effectiveness and the reliability of the approach.

Asymptotic Trajectory Tracking of Autonomous Bicycles via Backstepping and Optimal Control

This letter studies the trajectory tracking problem for an autonomous bicycle that is a non-minimum phase, strongly nonlinear system. As compared with most existing methods dealing only with approximate trajectory tracking, this letter proposes a constructive design to achieve asymptotic trajectory tracking. More specifically, under the assumption that the desired trajectory is generated by a virtual bicycle, a novel asymptotic trajectory tracking controller design scheme is presented. Firstly, the nonlinear dynamics of the autonomous bicycle is established. Secondly, it is decomposed into two interconnected subsystems: a tracking subsystem and a balancing subsystem. For the tracking subsystem, the popular backstepping approach is applied to determine the propulsive force of the bicycle. For the balancing subsystem, optimal control is applied to determine the steering angular velocity of the handlebar in order to balance the bicycle and align the bicycle with the desired yaw angle. Thirdly, to tackle the strong coupling between the tracking and the balancing systems, the small-gain technique is applied for the first time to prove the asymptotic stability of the closed-loop bicycle system. Finally, the efficacy of the proposed exact trajectory tracking control methodology is validated by numerical simulations.

Autocycle: Design, Construction, and Validation of an Autonomous Bicycle

Autocycle: Design, Construction, and Validation of an Autonomous Bicycle

A practical application of the geometrical theory on fibered manifolds to an autonomous bicycle motion in mechanical system with nonholonomic constraints

Abstract The equations of motion of a bicycle are highly nonlinear and rolling of wheels without slipping can only be expressed by nonholonomic constraint equations. A geometrical theory of general nonholonomic constrained systems on fibered manifolds and their jet prolongations, based on so-called Chetaev-type constraint forces, was proposed and developed in the last decade by O. Krupkova (Rossi) in 1990’s. Her approach is suitable for study of all kinds of mechanical systems-without restricting to Lagrangian, time-independent, or regular ones, and is applicable to arbitrary constraints (holonomic, semiholonomic, linear, nonlinear or general nonholonomic). The goal of this paper is to apply Krupkova’s geometric theory of nonholonomic mechanical systems to study a concrete problem in nonlinear nonholonomic dynamics, i.e., autonomous bicycle. The dynamical model is preserved in simulations in its original nonlinear form without any simplifying. The results of numerical solutions of constrained equations of motion, derived within the theory, are in good agreement with measurements and thus they open the possibility of direct application of the theory to practical situations.

Improving Energy Efficiency of an Autonomous Bicycle with Adaptive Controller Design

A method is proposed to achieve lateral stability of an autonomous bicycle with only the rotation of the front wheel. This can be achieved with a classic controller. However, if the energy consumption of the bicycle also has to be minimized, this solution is not valid. To solve this problem, an adaptive controller has been designed, which modifies its gains according to the bicycle’s forward velocity, adapting its response with minimum energy consumption and satisfying the design specifications. The study demonstrates the efficiency of the proposed control, achieving an energy saving of 73 . 8 % in trajectory tracking with respect to a conventional proportional-integral ( P I ) controller. These results show the importance of designing energy-efficient controllers, not only for autonomous vehicles but also for any automatic system where the energy consumption can be minimized.

Differential Transformation for Kinematic Modeling of Autonomous Bicycle

Differential Transformation for Kinematic Modeling of Autonomous Bicycle

Feasibility study of a sensor-based autonomous load control exercise training system for COPD patients.

Decision support systems (DSSs) which are able to automatically supervise and control physical exercise training of patients affected by chronic obstructive pulmonary disease (COPD) are regarded as a novel method to promote rehabilitation. The objective of our research work for this paper was to evaluate the feasibility of a rule-based DSS for autonomous bicycle ergometer training of COPD patients. Load control is based on real-time analysis of sensor parameters oxygen saturation and heart rate. Ten COPD patients have participated in a study, performing altogether 18 training sessions. On average, 7.4 rules were fired in each training session. Four sessions had to be stopped for different reasons. The average ergometer training load ranged between 31 and 47 W. The average percentage of heart rate in or lower than the intended target zone was 45.9 and 41.6%, respectively. The average patient-perceived Borg value was 12.6±2.4. Patients reported a high satisfaction for the automatically controlled training. With the help of the DSS, patients may change their training place from a rehabilitation center to their own homes. More studies are needed to assess long-term clinical and motivational effects of the DSS in home environment.

Trajectory planning and tracking control for autonomous bicycle robot

Control of the autonomous bicycle robot offers considerable challenges to the field of robotics due to its nonholonomic, underactuated, and nonminimum-phase properties. Furthermore, instability and complex dynamic coupling make the trajectory planning of the bicycle robot even more challenging. In this paper, we consider both trajectory planning and tracking control of the autonomous bicycle robot. The desired motion trajectory of the contact point of the bicycle’s rear wheel is constructed using the parameterized polynomial curve that can connect two given endpoints with associated tangent angles. The parameters of the polynomial curve are determined by minimizing the maximum of the desired roll angle’s equilibrium of the bicycle, and this optimization problem is solved by the particle swarm optimization algorithm. Then, a control scheme that can achieve full-state trajectory tracking while maintaining the bicycle’s balance is proposed by combining a planar trajectory tracking controller with a roll angle balance controller. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Robust control design of autonomous bicycle kinematics

In this paper, we provide a robust control approach for controlling the autonomous bicycle kinematics with the objective of stabilizing the bicycle steer $\delta$ and roll $\phi$ angles. The dynamical model is the so-called 'Whipples Bicycle Model', where the roll (lean) angle and the steer angle of the bicycle are the two outputs of the model and the torques across the roll and steer angle as the two control variables. Two control design methods are developed based on $H_\infty$ and $H_2$-norm optimization using dynamic output feedback. The ensuing results are compared with an adaptive control scheme. The autonomous bicycle was tested for varying velocities.

미소운동 변환을 이용한 자율주행 자전거의 기구학 모델

This paper presents a new method of kinematic modeling for autonomous bicycle by using the differential motion transformation. Kinematic model is indispensable to trajectory planning and control for an autonomous mobile robot. The conventional methods of kinematic modeling for an autonomous bicycle depend on intuition by geometry. On the contrary, the proposed method in this paper is based on the systematic differential motion transformation, thus applicable to various types of autonomous bicycles. The differential motion transformation gives Jacobian between two coordinate frames and the velocity kinematics as a result.

Control of an Autonomous Electric Bicycle with both Steering and Balancer Controls

In this paper, we propose a new cooperation control algorithm for stabilizing and trajectory tracking of an unmanned electric bicycle. The simplified model of the bicycle with the balancer is derived from Lagrangian and non-holonomic constraints with respect to translation and rotation relative to the ground plane. The stabilizing control and trajectory control of an autonomous bicycle are derived independently based on the simplified model. The balancing control is derived based on the output-zeroing controller. The steering and balancer for stabilizing the bicycle are used when the linear velocity is zero or the system starts up. It is shown that a balancing control using both the steering and the balancer has a better performance than conventional ones with only balancer or steering. The trajectory tracking control is derived by an input–output linearization approach to track the path in the ground plane. The steering and the back wheel are used to design the trajectory control. The coupling of the steering between the balancing control and the trajectory control are set by weighting gain. The balancing and the trajectory control have been implemented with the real bicycle by using MATLAB XPC-TARGET. An autonomous electric bicycle can be controlled remotely via a host PC. Numerical simulation and experimental results are shown to verify the effectiveness of the proposed control strategy.

Sliding-Mode Control Scheme for an Intelligent Bicycle

This paper deals with the robust stabilization and trajectory-tracking problems of a riderless bicycle. A dynamic model, which takes into account geometric-stabilization mechanisms due to bicycle trail, is presented. A posture controller which combines second-order sliding-mode control and disturbance observer is derived. Then, an innovative tracking controller based on the proposed posture controller and the dynamic-inversion framework is designed. Simulation and experimental results on an autonomous bicycle show the performances of the proposed strategy for the stabilization and tracking problems.

走行速度を考慮した自律走行自転車の軌道追従安定化走行制御(機械力学,計測,自動制御)

Many researchers have focused attention on a stability analysis and a stabilization control of a bicycle as one of controlled objects, because the bicycle is an unstable and nonlinear vehicle. A steering wheel control is needed to stabilize the bicycle. Moreover, a velocity of the bicycle can be controlled. Thereby, it is expected that the change of the running velocity affects the stability of the bicycle. In this study, the stabilization and trajectory tracking control of the bicycle considering the running velocity is proposed in order to improve the stability and the tracking performance. The simulations are carried out to verify the performance of the control system and the effectiveness of the change of the running velocity. From the simulation results, it was confirmed that the tracking performance and the stability against the disturbances are improved.

Stable Running Control of Autonomous Bicycle Robot

Bicycle is the unstable system in itself. Although there are two methods of steering a handle and moving a weight in order to make a bicycle stable, it is shown that the former is more effective than the latter. This study deals with modeling and stabilizing control problems of a two-wheel bicycle. In the modeling, wheels side slip is taken into consideration. In the control, an optimal feedback control for stable running control is obtained. An autonomous bicycle robot is further developed. As a result of experiment, it is shown that the bicycle robot is able to run straight and turn stably. The effectiveness of the two-wheel bicycle model and control law are demonstrated.

546 自律走行自転車ロボットの安定化走行制御

Bicycle is one of the most familiar vehicles in daily life, but it is a well-known unstable system in itself. Although there are two methods of steering a handle and moving a weight in order to make a bicycle stable, it is shown that the former is more effective than the latter. This study deals with modeling and stabilizing control problems of a two-wheel bicycle. In the modeling, wheels side slip is taken into consideration. In the control, an optimal feedback control for stable running control is obtained. An autonomous bicycle robot is further developed. As a result of experiment, it is shown that the bicycle robot is able to run straight and turn stably. The effectiveness of the two-wheel bicycle model and control law are demonstrated.

Point-to-point and collision avoidance control of the motion of an autonomous bicycle

This work deals with the stabilization and collision avoidance control of a riderless bicycle (see Figure 1). It is assumed here that the bicycle is controlled by a pedalling torque, a directional torque, and by a rotor mounted on the crossbar that generates a tilting torque. Given two points r A , r B , and a circular obstacle in the horizontal plane. Also, given a time interval [0, t f ], where 0 < t f < ∞. It is shown here that by applying a kind of inverse dynamics control, the motion of the bicycle is stabilized while simultaneously controlling its speed and direction in such a manner that the point of contact between the bicycle's rear wheel and the horizontal plane will be able, during [0, t f ], to move from r A to r B without hitting the obstacle.