There is an acute shortage of human coconut tree climbers to harvest coconuts in India and other developing countries. The consequential diminished availability of skilled tree-climbers, to pass along the trade secrets to the succeeding generations, highlights the exigent need for an unmanned coconut-tree-climber as an alternative solution. This research presents Amaran, a novel robotic coconut tree climber and harvester. Amaran is comprised of a harvester with a distinctive robotic arm (RA) and a cutter, which can be attached to a ring-shaped frame that can be fastened to a coconut tree. Amaran can be controlled, through a wireless interface, either by an operator on the ground or via a smartphone-based app. Once dispositioned in the vicinity of the coconut bunch, the cutter is commanded to harvest the coconuts, by cutting the stem of the bunch attached to the tree. Verification of the Amaran robot's viability was confirmed by tests conducted on a coconut tree setup in the design lab. Subsequently, the design of the Amaran robot was validated by field tests in a coconut farm. In this paper, we discuss the design of the Amaran body and the harvester. Amaran's dexterity in climbing and harvesting coconuts can be challenged by height, circumference, and inclination of the tree. Experimental results show that Amaran can successfully climb trees up to 15.2 m tall, of circumferences ranging from 0.66 m to 0.92 m, and tree trunk inclinations of up to 30 degrees.

Position and depth (PD) estimation is one of the key characteristics of autonomous robots. Robots are often challenged to visualize an alien environment remotely, alongside the control mechanism, and estimate the PD of objects. For the robot to reach out to an object, it needs to know the object's position in a 3-D space. The design of the robot's vision system is crucial. In this research work, we propose a human intervention-based hybrid approach for estimation of PD of an object. Human intervention in the form of a mouse click on the laser spot of the object image/in the video created by a camera-laser setup is used to estimate the PD of an object. An error correction model is developed and evaluated for better performance of the proposed method. A comparison of the proposed method with that of the image processing method revealed that a hybrid approach is almost 50% better in accuracy. The test results indicate that this method could be very helpful in finding the depth of the object with better accuracy in a teleoperated semiautonomous robot.

In this paper, we propose the design, development, and testing of high-torque and lightweight actuators suitable for lightweight robotic applications. The detailed design of the actuator module is described, and its performance evaluation is also presented. Further, the mathematical modelling of the actuator is discussed. Various performance analysis tests were carried out for the elucidation of the designed actuator, which included primarily position, velocity, and torque analyses. The position accuracy analysis included position repeatability at the maximum payload for calculating the acceptable tolerance. The velocity elucidation included a velocity test for the variable load. The torque analysis of the actuator was completed at different supply currents. These tests and the results indicate that the proposed actuator has high precision in reaching the desired position and provides a stabilized performance with variable loads up to the limit for which it was designed. Based on the torque output and the weight, the proposed actuator could be a good fit for lightweight robotic applications.

Mechanical energy harvesting, storage and utilization methods and devices are a little explored area with a potential to replace electrical energy in machines operated with electricity and which is environmentally friendly. Energy harvesting from human actions is an optimistic solution to provide energy supply. There are various methods and techniques that discuss energy harvesting from human actions. The problem is that most of these methods deal with tiny energy output. The object of this study is to design and characterize a flat spiral spring based method to harvest enough mechanical energy, to store and to drive a ride as in an amusement park instead of electricity. A flat spiral spring is specifically designed and fabricated for this purpose. To begin with, a life-size prototype of the kids' ride using the flat spiral spring is modeled, analyzed, fabricated and implemented on the kids' ride prototype. The stability of the ride is analyzed by modeling the impact of the collision between two kids' rides. Energy is harvested by winding the spring by hands using a handle or by pulling back the kids’ ride and is stored in the spring. Experimental results show that the proposed method of harvesting, storing and utilization of mechanical energy can be an alternative to electrical energy in operating high-power machines like kids' rides. An optimum width of 30 mm and a thickness of 1.4 mm for the flat spiral spring are found to help in ease of manufacturability, ease of rotation by human and compactness. The average force required to wind the spring is calculated to be 16.06 N, which is approximately 33 % of the force that can be exerted by a human hand. The stability of the proposed system in case of collision is verified by calculating the roll angle, which is less than 3.83 degrees, which is well below the recommended roll angle limit in case of collision.