Vision-based interface applied to assistive robots

This paper presents two vision-based interfaces for disabled people to command a mobile robot for personal assistance. The developed interfaces can be subdivided according to the algorithm of image processing implemented for the detection and tracking of two different body regions. The first interface detects and tracks movements of the user's head, and these movements are transformed into linear and angular velocities in order to command a mobile robot. The second interface detects and tracks movements of the user's hand, and these movements are similarly transformed. In addition, this paper also presents the control laws for the robot. The experimental results demonstrate good performance and balance between complexity and feasibility for real-time applications.Fil: Pérez Berenguer, María Elisa. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: López Celani, Natalia Martina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Nasisi, Oscar Herminio. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Mut, Vicente Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin

A vision-guided parallel parking system for a mobile robot using approximate policy iteration

Reinforcement Learning (RL) methods enable autonomous robots to learn skills from scratch by interacting with the environment. However, reinforcement learning can be very time consuming. This paper focuses on accelerating the reinforcement learning process on a mobile robot in an unknown environment. The presented algorithm is based on approximate policy iteration with a continuous state space and a fixed number of actions. The action-value function is represented by a weighted combination of basis functions. Furthermore, a complexity analysis is provided to show that the implemented approach is guaranteed to converge on an optimal policy with less computational time. A parallel parking task is selected for testing purposes. In the experiments, the efficiency of the proposed approach is demonstrated and analyzed through a set of simulated and real robot experiments, with comparison drawn from two well known algorithms (Dyna-Q and Q-learning)

Brain computer interface based robotic rehabilitation with online modification of task speed

We present a systematic approach that enables online modification/adaptation of robot assisted rehabilitation exercises by continuously monitoring intention levels of patients utilizing an electroencephalogram (EEG) based Brain-Computer Interface (BCI). In particular, we use Linear Discriminant Analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with motor imagery; however, instead of providing a binary classification output, we utilize posterior probabilities extracted from LDA classifier as the continuous-valued outputs to control a rehabilitation robot. Passive velocity field control (PVFC) is used as the underlying robot controller to map instantaneous levels of motor imagery during the movement to the speed of contour following tasks. In other words, PVFC changes the speed of contour following tasks with respect to intention levels of motor imagery. PVFC also allows decoupling of the task and the speed of the task from each other, and ensures coupled stability of the overall robot patient system. The proposed framework is implemented on AssistOn-Mobile - a series elastic actuator based on a holonomic mobile platform, and feasibility studies with healthy volunteers have been conducted test effectiveness of the proposed approach. Giving patients online control over the speed of the task, the proposed approach ensures active involvement of patients throughout exercise routines and has the potential to increase the efficacy of robot assisted therapies

GPS-guided mobile robot platform featuring modular design elements for agricultural applications : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University Turitea Campus, Palmerston North, New Zealand

The agricultural industry has not seen significant innovation in development of low-cost automated farming solutions, with current systems costing several thousands of dollars to implement. Currently these automated solutions are primarily implemented around crop planting and harvesting, and the large implementation cost of these systems makes them unfeasible for small-scale operations. Within many agricultural industries, workers expend a considerable amount of time undertaking simple tasks that are labour intensive. Many of these tasks could instead be completed using a self-driving robotic platform outfitted with the appropriate devices required for the tasks. This thesis covers the research work aiming to produce a solution that could turn an existing farming vehicle into a multipurpose low-cost agricultural platform, to act as the platform for an autonomous vehicle capable of performing pre-programmed tasks within an agricultural environment. A quad bike was selected as the vehicle platform for this research in which the control modules would control the speed and direction of this farm bike. Four modules were developed to control the vehicle components that would normally be operated by a human operator. These modules are comprised of mechanical actuators coupled with a microcontroller control system and includes some specific designs to maintain the user's ability to manually control the pre-existing systems. A gear-changing module controls the vehicles manual gearbox, providing a method to detect and control the vehicles current gear. A speed control module was developed to control the vehicles throttle and braking system and detects the vehicles speed. A steering module controls the vehicles steering system, allowing for accurate control of the vehicles direction. Finally, a vehicle controller module provides a central command interface that ties the previous three modules together and controls the vehicles electrical components and engine. Development of a low-cost differential GPS (DGPS) system was also undertaken to reduce the implementation cost of the system. Due to inconclusive results in relation to the positional accuracy of this system is was decided that a standard GPS system would be used for the vehicle prototype with further development on the DGPS system would be undertaken in future development of the research. The successful development of a farm automated vehicle platform was achieved through this research. With further improvement on software, intelligent control and the development of a low-cost differential global positioning satellite (GPS) system, a fully autonomous farm platform that can be outfitted with different tools or devices for the required farm tasks is feasible and practical

Wavefront Propagation and Fuzzy Based Autonomous Navigation

Path planning and obstacle avoidance are the two major issues in any navigation system. Wavefront propagation algorithm, as a good path planner, can be used to determine an optimal path. Obstacle avoidance can be achieved using possibility theory. Combining these two functions enable a robot to autonomously navigate to its destination. This paper presents the approach and results in implementing an autonomous navigation system for an indoor mobile robot. The system developed is based on a laser sensor used to retrieve data to update a two dimensional world model of therobot environment. Waypoints in the path are incorporated into the obstacle avoidance. Features such as ageing of objects and smooth motion planning are implemented to enhance efficiency and also to cater for dynamic environments

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Realization of reactive control for multi purpose mobile agents

Mobile robots are built for different purposes, have different physical size, shape, mechanics and electronics. They are required to work in real-time, realize more than one goal simultaneously, hence to communicate and cooperate with other agents. The approach proposed in this paper for mobile robot control is reactive and has layered structure that supports multi sensor perception. Potential field method is implemented for both obstacle avoidance and goal tracking. However imaginary forces of the obstacles and of the goal point are separately treated, and then resulting behaviors are fused with the help of the geometry. Proposed control is tested on simulations where different scenarios are studied. Results have confirmed the high performance of the method