We studied three types of lasers emitting narrow beam divergence of output light: 1) a spot-size converter integrated laser diodes (SS-LDs) with a vertically tapered waveguide, 2) one with a laterally tapered waveguide, and 3) one consisting of a small cross section of active region. We compared them with regard to their performance in coupling efficiency to a cleaved single mode fiber, threshold current, output power, and reliability. Both the spot-size converted integrated lasers with vertically and laterally tapered waveguide repeatedly provided low threshold currents of as low as 6 mA and low coupling loss to the fiber of 1.2 to 2.5 dB in two inch wafer processes. As a result of the aging test, the SS-lasers were predicted to have the same degradation rate as a conventional buried heterostructure laser. The laser having a small cross section of active layer also has low coupling loss and high efficiency up to 85.

The effect of well number in 1.3 µm GaInAsP Graded-Index Separate-Confinement-Heterostructure Multiple-Quantum-Well (GRIN-SCH-MQW) laser diodes (LDs) is examined experimentally in terms of threshold current density Jth, differential quantum efficiency ηd and internal loss α. For LDs with cavity length L of 270 µm, Jth as low as 0.9 KA/cm2 was obtained with 5 quantum wells. ηd as high as 81% and α as low as 5 cm-1 were obtained with 4 quantum wells. Taking these parameters into account, 4 or 5 is calulated to be the optimum number of quantum wells for the present structure, which was confirmed experimentally. Light output power of 56 mW/facet with a narrow and circular output beam was obtained in a buried heterostructure (BH) GRIN-SCH-MQW LD entirely grown by Metalorganic Chemical Vapor Deposition (MOCVD). These results indicate that the use of a GRIN-SCH in a MQW LD of the GaInAsP/InP system is effective in the improvement of laser characteristics.

To sustain and expand the agricultural economy even as its workforce shrinks, the efficiency of farm operations must be improved. One key to efficiency improvement is completely unmanned driving of farm machines, which requires stable monitoring and control of machines from remote sites, a safety system to ensure safe autonomous driving even without manual operations, and precise positioning in not only small farm fields but also wider areas. As possible solutions for those issues, we have developed technologies of wireless network quality prediction, an end-to-end overlay network, machine vision for safety and positioning, network cooperated vehicle control and autonomous tractor control and conducted experiments in actual field environments. Experimental results show that: 1) remote monitoring and control can be seamlessly continued even when connection between the tractor and the remote site needs to be switched across different wireless networks during autonomous driving; 2) the safety of the autonomous driving can automatically be ensured by detecting both the existence of people in front of the unmanned tractor and disturbance of network quality affecting remote monitoring operation; and 3) the unmanned tractor can continue precise autonomous driving even when precise positioning by satellite systems cannot be performed.