Towards a Mobile-Robot Following Controller Using Behavioral Cues
This paper describes work towards a mobile-robot following controller which has the ability to incorporate a leader's behavioral cues into its controller formulation. The paper presents the mathematical formulation of the controller, and presents robot experimental studies used to investigate the controller. The controller continuously estimates the future predicted position of the leader (robot or human) as he/she/it moves, and then directs the follower robot to this position. A Kalman filter is employed for estimation that uses vision-based measurements of leader position, a dynamics model of the leader, and a behavioral-cue model of the leader. Singer's model is used to propagate the leader's state. A behavioral-cue model serves to create pseudo-measurements to further help the Kalman filter estimate the leader's future position. The controller is implemented on an ER Scorpion robot. Experiments are conducted using several different controllers. Results demonstrate that compared to other controllers, the proposed controller can more consistently follow the leader around sharp corners where line-of-sight is lost, as can happen often in indoor environments. However, in cases of more gradual movement where line-of-sight is not lost, a simpler vision-only controller has advantages.
[Show abstract] [Hide abstract] ABSTRACT: This paper describes a practical study of basic line follower wheeled mobile robot implemented during practical class for mechanical engineering students. The basic mobile robot from DIY KITS is used as an introductory-level differential wheeled mobile robot (DWMR) for students to get started in building mobile robot. The mini mobile robot controller, MC40A, combined with LSS05 auto-calibrate line sensor will develop the line follower DWMR. The sensor indication and DWMR wheel reaction is presented in this paper based on the black line follower mode. Several tracks are designed for multi tasking line follower DWMR to obtain the performance of line follower characteristics.0Comments 1Citation
- "e avoidance and target seeking mobile robot based on fuzzy logic. Fuzzy logic control laws for differential steering control of the autonomous non-holonomic mobile robot were developed by Saidon et al. (2011) in order to accurately measure the location of a target in real world coordinates and finds the distance to the target from the mobile robot. Chueh (2006) described the work on mobile robot controller involving the mathematical formulation including Kalman filter and presented the experimental study on mobile robot controller. The proposed controller shows a better performance when compared with other controllers. Pakdaman (2010) present an investigation involving the technical and mechan"
- [Show abstract] [Hide abstract] ABSTRACT: Robots are poised to enter our everyday environments such as our homes and offices. These contexts present unique human demands, including questions of the style and personality of the robot's actions. Style-oriented characteristics are difficult to define programmatically, and as such, are often out of reach from the designers involved in creating robotic technologies. This problem is particularly prominent for a robot's interactive behaviors, those that must react accordingly to dynamic environments and actions of people. In this paper, we present the concept of programming robotic style by demonstration through the use of broomsticks and tangibles, such that non-technical designers can directly create the style of actions using their existing skill sets. We developed a working system as a proof-of-concept, and present two novel interfaces for directly demonstrating the style of motions to robots. Our current focus is on the style of a robot following a person, but we envision that simple physical interfaces like ours can be used by non-technical people to design the style of a wide range of robotic behaviors.0Comments 2Citations
- [Show abstract] [Hide abstract] ABSTRACT: This paper proposes an autonomous-robot following controller that can integrate information provided from behavioral cues of the leader to increase the reliability and the performance of following. The controller continuously estimates the future predicted position of the leader as it moves, and then directs the follower robot to this position. A Kalman filter is employed for an estimation that uses vision-based measurements of leader position, a dynamic model of the leader, and a behavioral-cue model of the leader. The behavioral-cue model serves to either tune the dynamic model and/or create pseudomeasurements to further help the Kalman filter estimate the leader's future position. Once the leader's future position is estimated, a trajectory planner plans a path to the future position, and a motor controller implements the required control signals to the robot wheels. It is suggested that this controller may have particular importance for human following by autonomous robots in future human-robot interaction environments.0Comments 29Citations