Chong Hui Kim

Robotic smart house to assist people with movement disabilities

This paper introduces a new robotic smart house, Intelligent Sweet Home, developed at KAIST in Korea, which is based on several robotic agents and aims at testing advanced concepts for independent living of the elderly and people with disabilities. The work focuses on technical solutions for human-friendly assistance in motion/mobility and advanced human-machine interfaces that provide simple control of all assistive robotic systems and home-installed appliances. The smart house concept includes an intelligent bed, intelligent wheelchair, and robotic hoist for effortless transfer of the user between bed and wheelchair. The design solutions comply with most of the users’ requirements and suggestions collected by a special questionnaire survey of people with disabilities. The smart house responds to the users commands as well as to the recognized intentions of the user. Various interfaces, based on hand gestures, voice, body movement, and posture, have been studied and tested. The paper describes the overall system structure and explains the design and functionality of some main system components.

Minimum-Energy Translational Trajectory Generation for Differential-Driven Wheeled Mobile Robots

Mobile robots can be used in many applications, such as exploration, search and rescue, reconnaissance, security, and cleaning. Mobile robots usually carry batteries as their energy source and their operational time is restricted by the finite energy available from the batteries. Therefore, energy constraints are critical to the service time of mobile robots. This paper investigates the minimum-energy control problem for translational trajectory generation, which minimizes the energy drawn from the batteries. Optimal control theory is used to find the optimal velocity trajectory in analytic form. To demonstrate energy efficiency obtainable, we performed simulations of minimum-energy velocity control and compared the results with loss-minimization control and energy-optimal trapezoidal velocity profiles. Simulation results showed that significant energy savings can be achieved, of up to 9% compared with loss-minimization control and up to 10% compared with energy-optimal trapezoidal velocity profile. We also performed an actual robot experiment using Pioneer 3-AT platform to show the validity of the proposed minimum-energy velocity control. The experimental results revealed that the proposed minimum-energy velocity control can save the battery energy up to 10% compared with loss-minimization control.

Energy-Saving 3-Step Velocity Control Algorithm for Battery-Powered Wheeled Mobile Robots

Energy of Wheeled Mobile Robot (WMR) is usually supplied by batteries with finite energy. In order to extend run-time of battery-powered WMR, it is necessary to minimize the energy consumption. The energy is dissipated mostly in the motors, which strongly depends on the velocity profile. This paper investigates energy efficiency for typical 3-step velocity control methods to minimize a new energy object function which considers practical energy consumption dissipated in motors related to motor dynamics, velocity profile, and motor control input. We performed analyses on energy consumption for the four typical 3-step velocity profiles: S-C-S, T-C-T, S-C-T, and T-C-S (S is an acceleration/deceleration section by step control input, T is an acceleration/deceleration section by acceleration/deceleration phase of trapezoidal velocity profile, and C is a cruise section with a constant velocity). Also we suggested an efficient iterative search algorithm with binary search which can find the numerical solution quickly. We performed various computer simulations to show the performance of energy-efficient 3-step velocity control in comparison with a conventional 3-step trapezoidal profile with a reasonable constant acceleration rate as a benchmark. Simulation results reveal that the S-C-T is the most energy efficient 3-step velocity control profile, which enables WMR to extend working time up to 30%.

Minimum-Energy Motion Planning for Differential-Driven Wheeled Mobile Robots

With the remarkable progresses in robotics, mobile robots can be used in many applications including exploration in unknown areas, search and rescue, reconnaissance, security, military, rehabilitation, cleaning, and personal service. Mobile robots should carry their own energy source such as batteries which have limited energy capacity. Hence their applications are limited by the finite amount of energy in the batteries they carry, since a new supply of energy while working is impossible, or at least too expensive to be realistic. ASIMO, Honda’s humanoid robot, can walk for only approximately 30 min with its rechargeable battery backpack, which requires four hours to recharge (Aylett, 2002). The BEAR robot, designed to find, pick up, and rescue people in harm’s way, can operate for approximately 30 min (Klein et al., 2006). However, its operation time is insufficient for complicated missions requiring longer operation time. Since operation times of mobile robots are mainly restricted by the limited energy capacity of the batteries, energy conservation has been a very important concern for mobile robots (Makimoto & Sakai, 2003; Mei et al., 2004; Spangelo & Egeland, 1992; Trzynadlowski, 1988; Zhang et al., 2003). Rybski et al. (Rybski et al., 2000) showed that power consumption is one of the major issues in their robot design in order to survive for a useful period of time. Mobile robots usually consist of batteries, motors, motor drivers, and controllers. Energy conservation can be achieved in several ways, for example, using energy-efficient motors, improving the power efficiency of motor drivers, and finding better trajectories (Barili et al., 1995; Mei et al., 2004; Trzynadlowski, 1988; Weigui et al., 1995). Despite efficiency improvements in the motors and motor drivers (Kim et al., 2000; Leonhard, 1996), the operation time of mobile robots is still limited in their reliance on batteries which have finite energy. We performed experiments with mobile robot called Pioneer 3-DX (P3-DX) to measure the power consumption of components: two DC motors and one microcontroller which are major energy consumers. Result shows that the power consumption by the DC motors accounts for more than 70% of the total power. Since the motor speed is largely sensitive to torque variations, the energy dissipated by a DC motor in a mobile robot is critically dependent on its velocity profile. Hence energy-optimal motion planning can be achieved by determining the optimal velocity profile and by controlling the mobile robot to follow that trajectory, which results in the longest working time possible.