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This work presents an IR-based system for parking assistance and obstacle detection in the automotive field that employs the Microsoft Kinect camera for fast 3D point cloud reconstruction. In contrast to previous research that attempts to explicitly identify obstacles, the proposed system aims to detect "reachable regions" of the environment, i.e., those regions where the vehicle can drive to from its current position. A user-friendly 2D traversability grid of cells is generated and used as a visual aid for parking assistance. Given a raw 3D point cloud, first each point is mapped into individual cells, then, the elevation information is used within a graph-based algorithm to label a given cell as traversable or non-traversable. Following this rationale, positive and negative obstacles, as well as unknown regions can be implicitly detected. Additionally, no flat-world assumption is required. Experimental results, obtained from the system in typical parking scenarios, are presented showing its effectiveness for scene interpretation and detection of several types of obstacle.
parking assistance; kinect sensor; traversability map in urban environments, intelligent vehicles; driving automation
Mauro Bellone, Luca Pascali and Giulio Reina:
Department of Engineering for Innovation, Università del Salento, Via Arnesano, 73100 Lecce, Italy.
Redundant parallel manipulators have some advantages over the nonredundant parallel manipulators. It is important to determine how many additional branches should be introduced. This paper studies whether one or two additional branches should be added to a 3-DOF parallel manipulator by comparing the flexible deformation of a 3-DOF parallel manipulator with one additional branch and that with two additional branches. The kinematic and dynamic models of the redundant parallel manipulator are derived and the flexible deformation is investigated. The flexible deformation of the manipulators with one additional branch and two branches is simulated and compared. This paper is helpful for designers to design a redundantly actuated parallel manipulator.
parallel manipulator; flexible deformation; principal of virtual work; dynamics
(1) Xiaolei Chen, Jun Wu, Guang Yu and Liping Wang:
Institute of Manufacturing Engineering, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
(2) Xiaolei Chen, Jun Wu, Guang Yu and Liping Wang:
Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Beijing 100084, China.
Study results in the last decades show that amount and quality of physical exercises, then the active participation, and now the cognitive involvement of patient in rehabilitation training are known of crux to enhance recovery outcome of motor dysfunction patients after stroke. Rehabilitation robots mainly have been developing along this direction to satisfy requirements of recovery therapy, or focusing on one or more of the above three points. Therefore, neuro-machine interaction based active rehabilitation robot has been proposed for assisting paralyzed limb performing designed tasks, which utilizes motor related EEG, UCSDI (Ultrasound Current Source Density Imaging), EMG for rehabilitation robot control and feeds back the multi-sensory interaction information such as visual, auditory, force, haptic sensation to the patient simultaneously. This neuro-controlled and perceptual rehabilitation robot will bring great benefits to post-stroke patients. In order to develop such kind of robot, some key technologies such as noninvasive precise detection of neural signal and realistic sensation feedback need to be solved. There are still some grand challenges in solving the fundamental questions to develop and optimize such kind of neuro-machine interaction based active rehabilitation robot.
rehabilitation robot; neuro-machine interaction; active rehabilitation therapy; multi-sensation feedback
Aiguo Song, Renhuan Yang, Baoguo Xu, Lizheng Pan and Huijun Li:
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, P.R. China.
Distributed planning and decision making can be beneficial from the robustness, adaptability and fault tolerance in multi-robot systems. Distributed mechanisms have not been employed in three dimensional transportation systems namely aerial and underwater environments. This paper presents a distributed cooperation mechanism on multi robot transportation problem in three dimensional environments. The cooperation mechanism is based on artificial capital market, a newly introduced market based negotiation protocol. In the proposed mechanism contributing in transportation task is defined as asset. Each robot is considered as an investor who decides if he is going to invest on some assets. The decision is made based on environmental constraint including fuel limitation and distances those are modeled as capital and cost. Simulations show effectiveness of the algorithm in terms of robustness, speed and adaptability.
multi-robot transportation; multiagent cooperation; market mechanism; artificial capital market
(1) Adel Akbarimajd:
Department of Electrical Engineering, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabil, Iran;
(2) Ghader Simzan:
Department of Electrical Engineering, Islamic Azad University, Meshkin Shahr Branch, Iran.